BibTex:

    @Article{OJIOT_2024v9i1n01_Aguilar,
        title     = {Towards Sustainable Smart Cities: Monitoring Air Quality and Comfort for Citizen Health},
        author    = {Jaime Fabian Arias Aguilar and
                     Everton Gomede and
                     Leonardo de Sousa Mendes},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2024},
        volume    = {9},
        number    = {1},
        pages     = {1--25},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2410201933069.818732022293},
        urn       = {urn:nbn:de:101:1-2410201933069.818732022293},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In smart city development, addressing air pollution and climate change through advanced environmental monitoring systems is crucial for enhancing urban quality of life and public health. This study focuses on the architecture of an intelligent system designed for real-time environmental monitoring in smart cities. The system aims to improve urban quality of life by addressing air pollution and climate change and assessing their impact on public health. The proposed system uses Arduino technology and integrated sensors to monitor PM10, PM2.5, toxic gases, and temperature. It incorporates a database in InfluxDB and Node-RED for efficient data management and visualization. The analysis employs the Knowledge Discovery in Data (KDD) methodology, Principal Component Analysis (PCA), and the DBSCAN algorithm for clustering high-pollution areas. The findings highlight the significant impact of air quality variables on environmental comfort. The system effectively identifies areas with high pollution levels, enabling informed urban planning and decision-making. In conclusion, this study emphasizes the need for effective air quality management and cross-sector collaboration to create healthier urban environments. The intelligent system demonstrates the potential for enhancing environmental comfort and addressing the environmental challenges of modern cities.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n01e_VLIOT2022,
        title     = {Contributions to the 6th Workshop on Very Large Internet of Things (VLIoT 2022)},
        author    = {Sven Groppe and
                     Sanju Tiwari and
                     Shui Yu},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {1--6},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515500516853039},
        urn       = {urn:nbn:de:101:1-2022090515500516853039},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The concept of the Internet of Things, where small things become available in the Internet and get connected with each other for the purpose of advanced applications, raises many new open challenges to research. This even increases when considering large-scale Internet-of-Things (IoT) configurations, which is the focus of our Very Large Internet of Things (VLIoT) workshop. We recognize that the IoT research community is very active and the industry continuously develops novel IoT applications for daily live. Hence we received many high-quality submissions, from which we accepted 7 to be introduced in this editorial.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n02_Leon,
        title     = {Development and Evaluation of a Publish/Subscribe IoT Data Sharing Model with LoRaWAN},
        author    = {Juan Leon and
                     Yacoub Hanna and
                     Kemal Akkaya},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {7--19},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515501014226277},
        urn       = {urn:nbn:de:101:1-2022090515501014226277},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Publish/subscribe architectures are becoming very common for many IoT environments such as power grid, manufacturing and factory automation. In these architectures, many different communication standards and middleware can be supported to ensure interoperability. One of the widely used publish/subscribe protocol is MQTT where a broker acts among publishers and subscribers to relay data on certain topics. While MQTT can be easily setup on cloud environments to perform research experiments, its large-scale and quick deployment for IoT environments with a widely used wireless MAC layer protocol such as LoRaWAN has not been thoroughly tested. Therefore, in this paper we develop and present a simulation framework in NS-3 to offer MQTT-based on publish/subscribe architecture that can also support LoRaWAN communication standard. To this end, we utilize NS-3's LoRaWAN library and integrate it with a broker that connects to other types of publishers/subscribers. We enable unicast capability from the broker to LoRaWAN end-devices while supporting multiple topics at the broker. We tested several scenarios under this IoT architecture to demonstrate its feasibility while assessing the performance at scale.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n03_Ziehn,
        title     = {IoT-PMA: Patient Health Monitoring in Medical IoT Ecosystems},
        author    = {Ariane Ziehn and
                     Christian Mandel and
                     Kathrin Stich and
                     Rolf Dembinski and
                     Karin Hochbaum and
                     Steffen Zeuch and
                     Volker Markl},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {20--31},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515501651013147},
        urn       = {urn:nbn:de:101:1-2022090515501651013147},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The emergence of the Internet of Things (IoT) and the increasing number of cheap medical devices enable geographically distributed healthcare ecosystems of various stakeholders. Such ecosystems contain different application scenarios, e.g., (mobile) patient monitoring using various vital parameters such as heart rate signals. The increasing number of data producers and the transfer of data between medical stakeholders introduce several challenges to the data processing environment, e.g., heterogeneity and distribution of computing and data, lowlatency processing, as well as data security and privacy. Current approaches propose cloud-based solutions introducing latency bottlenecks and high risks for companies dealing with sensitive patient data. In this paper, we address the challenges of medical IoT applications by proposing an end-to-end patient monitoring application that includes NebulaStream as the data processing system, an easy-to-use UI that provides ad-hoc views on the available vital parameters, and the integration of ML models to enable predictions on the patients' health state. Using our end-to-end solution, we implement a real-world patient monitoring scenario for hemodynamic and pulmonary decompensations, which are dynamic and life-threatening deteriorations of lung and cardiovascular functions. Our application provides ad-hoc views of the vital parameters and derived decompensation severity scores with continuous updates on the latest data readings to support timely decision-making by physicians. Furthermore, we envision the infrastructure of an IoT ecosystem for a multi-hospital scenario that enables geo-distributed medical participants to contribute data to the application in a secure, private, and timely manner.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n04_Yuan,
        title     = {3D Histogram Based Anomaly Detection for Categorical Sensor Data in Internet of Things},
        author    = {Peng Yuan and
                     Lu-An Tang and
                     Haifeng Chen and
                     Moto Sato and
                     Kevin Woodward},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {32--43},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515502212539652},
        urn       = {urn:nbn:de:101:1-2022090515502212539652},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The applications of Internet-of-things (IoT) deploy massive number of sensors to monitor the system and environment. Anomaly detection on streaming sensor data is an important task for IoT maintenance and operation. In real IoT applications, many sensors report categorical values rather than numerical readings. Unfortunately, most existing anomaly detection methods are designed only for numerical sensor data. They cannot be used to monitor the categorical sensor data. In this study, we design and develop a 3D Histogram based Categorical Anomaly Detection (HCAD) solution to monitor categorical sensor data in IoT. HCAD constructs the histogram model by three dimensions: categorical value, event duration, and frequency. The histogram models are used to profile normal working states of IoT devices. HCAD automatically determines the range of normal data and anomaly threshold. It only requires very limit parameter setting and can be applied to a wide variety of different IoT devices. We implement HCAD and integrate it into an online monitoring system. We test the proposed solution on real IoT datasets such as telemetry data from satellite sensors, air quality data from chemical sensors, and transportation data from traffic sensors. The results of extensive experiments show that HCAD achieves higher detecting accuracy and efficiency than state-of-the-art methods.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n05_Misev,
        title     = {Space Cubes: Satellite On-Board Processing of Datacube Queries},
        author    = {Dimitar Misev and
                     Peter Baumann},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {44--53},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515502699550987},
        urn       = {urn:nbn:de:101:1-2022090515502699550987},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Datacubes form an accepted cornerstone for analysis- and visualization-ready spatio-temporal data offerings. The increase in user friendliness is achieved by abstracting away from the zillions of files in provider-specific organization. Datacube query languages additionally establish actionable datacubes, enabling users to ask "any query, any time" with zero coding. However, typically datacube deployments are aiming at large scale, data center environments accommodating Big Data and massive parallel processing capabilities for achieving decent performance. In this contribution, we conversely report about a downscaling experiment. In the ORBiDANSE project a datacube engine, rasdaman, has been ported to a cubesat, ESA OPS-SAT, and is operational in space. Effectively, the satellite thereby becomes a datacube service offering the standards-based query capabilities of the OGC Web Coverage Processing (WCPS) geo datacube analytics language. We believe this will pave the way for on-board ad-hoc processing and filtering on Big EO Data, thereby unleashing them to a larger audience and in substantially shorter time.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n06_Cimmino,
        title     = {WoTHive: Enabling Syntactic and Semantic Discovery in the Web of Things},
        author    = {Andrea Cimmino and
                      Ra\'{u}l Garc\'{i}a-Castro},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {54--65},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515503251402854},
        urn       = {urn:nbn:de:101:1-2022090515503251402854},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In the last decade the Internet of Things (IoT) has experienced a significant growth and its adoption has become ubiquitous in either business and private life. As a result, several initiatives have emerged for addressing specific challenges and provide a standard or a specification to address them; like CoRE, Web of Things (WoT), oneM2M, or OGC among others. One of these challenges revolves around the discovery procedures to find IoT devices within IoT infrastructures and whether the discovery performed is semantic or syntactic. This article focusses on the WoT initiative and reports the benefits that Semantic Web technologies bring to discovery in WoT. In particular, one of the implementations for the WoT discovery is presented, which is named WoTHive and provides syntactic and semantic discovery capabilities. WoTHive is the only candidate implementation that addresses at the same time the syntactic and semantic functionalities specified in the discovery described by WoT. Several experiments have been carried out to test WoTHive; these advocate that the implementation is technically sound for CRUD operations and that its semantic discovery outperforms the syntactic one implemented. Furthermore, an experiment has been carried out to compare whether syntactic discovery is faster than semantic discovery using the Link Smart implementation for syntactic discovery and WoTHive for semantic.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n07_Khaled,
        title     = {IoT Hub as a Service (HaaS): Data-Oriented Environment for Interactive Smart Spaces},
        author    = {Ahmed E. Khaled and
                     Rousol Al Goboori},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {66--79},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515503839588667},
        urn       = {urn:nbn:de:101:1-2022090515503839588667},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Smart devices around us produce a considerable volume of data and interact in a wide range of scenarios that guide the evolution of the Internet of Things (IoT). IoT adds informative and interactive aspects to our living spaces, converting them into smart spaces. However, the development of applications is challenged by the fragmented nature due to the vast number of different IoT things, the format of reported information, communication standards, and the techniques used to design applications. This paper introduces IoT Hub as a Service (HaaS), a data-oriented framework to enable communication interoperability between the ecosystem's entities. The framework abstracts things' information, reported data items, and developers' applications into programmable objects referred to as Cards. Cards represent specific entities and interactions of focus with meta-data. The framework then indexes cards' meta-data to enable interoperability, data management, and application development. The framework allows users to create virtual smart spaces (VSS) to define cards' accessibility and visibility. Within VSS, users can identify accessible data items, things to communicate, and authorized applications. The framework, in this paper, defines four types of Cards to represent: participating IoT things, data items, VSS, and applications. The proposed framework enables the development of synchronous and asynchronous applications. The framework dynamically creates, updates, and links the cards throughout the life-cycle of the different entities. We present the details of the proposed framework and show how our framework is advantageous and applicable.}
    }

BibTex:

    @Article{OJIOT_2022v8i1n08_Paasche,
        title     = {Generating SPARQL-Constraints for Consistency Checking in Industry 4.0 Scenarios},
        author    = {Simon Paasche and
                     Sven Groppe},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2022},
        volume    = {8},
        number    = {1},
        pages     = {80--90},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2022090515504409042979},
        urn       = {urn:nbn:de:101:1-2022090515504409042979},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {A smart manufacturing line consists of multiple connected machines. These machines communicate with each other over a network, to solve a common task. Such a scenario can be located in the Internet of Things (IoT) area. An individual machine can be perceived as an IoT device. Due to machine to machine communication, a huge amount of data is generated during manufacturing. This emerging data flow is an essential part of today's industry, as analyzing data helps improving processes and thus, product quality. To adequately make use of the collected data, we require a high level of data quality. In our work, we address the issue of inconsistent data in smart manufacturing and present an approach to automatically generate SPARQL queries for validation.}
    }

BibTex:

    @Article{OJIOT_2021v7i1n01_Madjarov,
        title     = {A Graph-Based Web Services Discovery Framework for IoT EcoSystem},
        author    = {Ivan Madjarov and
                     Fatma Slaimi},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2021},
        volume    = {7},
        number    = {1},
        pages     = {1--17},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2021050919331013194824},
        urn       = {urn:nbn:de:101:1-2021050919331013194824},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Nowadays, the Internet of Things (IoT) represents an important topic and research domain with multiple objectives. However, most IoTs communicate poorly across the multitude of network interfaces. It should be preferably used a single universal application layer protocol for the devices and services interconnection, regardless of how they are physically connected. The IoT paradigm boosts the device connectivity and the user accessibility benefits of services introduced within the network of connected objects associated with a context-awareness. Within this frame of reference, Web service is the appropriate technological approach to exhibit a set of related IoT functionalities loosely coupled with other services discovered or composed through the Web. In this work, we consider the heterogeneity of connecting technologies for IoT and the applications and devices integration in a single interoperable framework as a research objective. With this in mind, we introduce a five layers multigraph model for Web Services discovery and recommendation, and we address Web services-based applications for IoT data integration. The launched service discovery process permits the interaction between the user/application and the IoT environment. In this context, the choice of suitable services represents a challenge that covers the functionality and the required quality to combine composite services, namely mashups for IoT data management and interconnection. For proof of concept, we test a RESTful Web Services framework as an experimental platform to animate a graph-based approach for dynamic IoT  services discovery. We develop a recommender system that performs graph analytics to produce a set of services according to the user's request. The quality of the recommendation process is evaluated by analyzing the correlation of user satisfaction.}
    }

BibTex:

    @Article{OJIOT_2021v7i1n02e_VLIoT2021,
        title     = {Overview of the 2021 Edition of the Workshop on Very Large Internet of Things (VLIoT 2021)},
        author    = {Sven Groppe and
                     Weizhi Meng},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2021},
        volume    = {7},
        number    = {1},
        pages     = {18--22},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2021082919330413733202},
        urn       = {urn:nbn:de:101:1-2021082919330413733202},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The Very Large Internet of Things (VLIoT) workshop aims at discussing the solutions of problems arising especially for large-scale Internet-of-Things (IoT) configurations. After online conferences and workshops are becoming the normal mode for running scientific events, after continuously monitoring the global COVID-19 pandemic this year with falling incidence rates in the last times due to vaccination successes, the workshop changes the format the first time to a hybrid event. This ensures that still problems are overcome like travel restrictions, but offers face-to-face discussions among those going to the local event. A hybrid format has still chances like an increased number of participants, less travel burdens and saving budget, but offers the possibility for going to the local event already for a large portion of the participants. Hence we received many high-quality submissions, from which we accepted 9 to be introduced in this editorial.}
    }

BibTex:

    @Article{OJIOT_2021v7i1n03_Rong,
        title     = {Video Source Forensics for IoT Devices Based on Convolutional Neural Networks},
        author    = {Dongzhu Rong and
                     Yan Wang and
                     Qindong Sun},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2021},
        volume    = {7},
        number    = {1},
        pages     = {23--31},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2021082919330983129965},
        urn       = {urn:nbn:de:101:1-2021082919330983129965},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {With the wide application of Internet of things devices and the rapid development of multimedia technology, digital video has become one of the important information dissemination carriers among Internet of things devices, and it has been widely used in many fields such as news media, digital forensics and so on. However, the current video editing technology is constantly developing and improving, which seriously threatens the integrity and authenticity of digital video. Therefore, the research on digital video forensics has a great significance. In this paper, a new video source passive forensics algorithm based on Convolutional Neural Networks(CNN) is proposed. CNN is used to classify the maximum information block of specified size in video I frame, and then the classification results are fused to determine the camera to which the video belongs. Experimental results show that the recognition algorithm proposed in this paper has a better performance than other methods in trems of accuracy and ROC curve. And our method still can have a good recognition effect even if a small number of I frames are used for recognition.}
    }

BibTex:

    @Article{OJIOT_2021v7i1n04_Fuerst,
        title     = {Realizing the Digital Twin Transition for Smart Cities},
        author    = {Jonathan F{\"u}rst and
                     Bin Cheng and
                     Benjamin Hebgen},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2021},
        volume    = {7},
        number    = {1},
        pages     = {32--42},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2021082919331474662784},
        urn       = {urn:nbn:de:101:1-2021082919331474662784},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The digital twin transition for cities is expected to improve, among others, living quality, carbon footprint and generate new business opportunities across different organizations. However, as cities consist of many separate entities that are in close and frequent interaction with each other, it is not possible to simply apply digital twin concepts from the engineering and manufacturing domains in a silo-ed fashion for each entity. In this paper, we distill the requirements and challenges to develop digital twins for smart cities based on a typical smart city use case. We follow with a first systematic approach to address them in a data-driven fashion to realize the digital twin transition for cities.}
    }

BibTex:

    @Article{OJIOT_2021v7i1n05_Loseto,
        title     = {A Mobile and Web Platform for Crowdsourcing OBD-II Vehicle Data},
        author    = {Giuseppe Loseto and
                     Filippo Gramegna and
                     Agnese Pinto and
                     Michele Ruta and
                     Floriano Scioscia},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2021},
        volume    = {7},
        number    = {1},
        pages     = {43--58},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2021082919332057007441},
        urn       = {urn:nbn:de:101:1-2021082919332057007441},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {On-Board Diagnostics 2 (OBD-II) protocol allows monitoring vehicle status parameters. Analyzing them is highly useful for Intelligent Transportation Systems (ITS) research, applications and services. Unfortunately, large-scale OBD datasets are not publicly available due to the effort of producing them as well as due to competitiveness in the automotive sector. This paper proposes a framework to enable a worldwide crowdsourcing approach to the generation of OBD-II data, similarly to OpenStreetMap (OSM) for cartography. The proposal comprises: (i) an extension of the GPX data format for route logging, augmented with OBD-II parameters; (ii) a fork of an open source Android OBD-II data logger to store and upload route traces, and (iii) a Web platform extending the OSM codebase to support storage, search and editing of traces with embedded OBD data. A full platform prototype has been developed and early scalability tests have been carried out in various workloads to assess the sustainability of the proposal.}
    }

BibTex:

    @Article{OJIOT_2021v7i1n06_Giouroukis,
        title     = {Streaming Data through the IoT via Actor-Based Semantic Routing Trees},
        author    = {Dimitrios Giouroukis and
                     Johannes Jestram and
                     Steffen Zeuch and
                     Volker Markl},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2021},
        volume    = {7},
        number    = {1},
        pages     = {59--70},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2021082919332566828749},
        urn       = {urn:nbn:de:101:1-2021082919332566828749},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The Internet of Things (IoT) enables the usage of resources at the edge of the network for various data management tasks that are traditionally executed in the cloud. However, the heterogeneity of devices and communication methods in a multi-tiered IoT environment (cloud/fog/edge) exacerbates the problem of deciding which nodes to use for processing and how to route data. In addition, both decisions cannot be made only statically for the entire lifetime of an application, as an IoT environment is highly dynamic and nodes in the same topology can be both stationary and mobile as well as reliable and volatile. As a result of these different characteristics, an IoT data management system that spans across all tiers of an IoT network cannot meet the same availability assumptions for all its nodes. To address the problem of choosing ad-hoc which nodes to use and include in a processing workload, we propose a networking component that uses a-priori as well as ad-hoc routing information from the network. Our approach, called Rime, relies on keeping track of nodes at the gateway level and exchanging routing information with other nodes in the network. By tracking nodes while the topology evolves in a geo-distributed manner, we enable efficient communication even in the case of frequent node failures. Our evaluation shows that Rime keeps in check communication costs and message transmissions by reducing unnecessary message exchange by up to 82:65\%.}
    }

BibTex:

    @Article{OJIOT_2021v7i1n07_Chatziliadis,
        title     = {Monitoring of Stream Processing Engines Beyond the Cloud: An Overview},
        author    = {Xenofon Chatziliadis and
                     Eleni Tzirita Zacharatou and
                     Steffen Zeuch and
                     Volker Markl},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2021},
        volume    = {7},
        number    = {1},
        pages     = {71--82},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2021082919333128288412},
        urn       = {urn:nbn:de:101:1-2021082919333128288412},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The Internet of Things (IoT) is rapidly growing into a network of billions of interconnected physical devices that constantly stream data. To enable data-driven IoT applications, data management systems like NebulaStream have emerged that manage and process data streams, potentially in combination with data at rest, in a heterogeneous distributed environment of cloud and edge devices. To perform internal optimizations, an IoT data management system requires a monitoring component that collects system metrics of the underlying infrastructure and application metrics of the running processing tasks. In this paper, we explore the applicability of existing cloud-based monitoring solutions for stream processing engines in an IoT environment. To this end, we provide an overview of commonly used approaches, discuss their design, and outline their suitability for the IoT. Furthermore, we experimentally evaluate different monitoring scenarios in an IoT environment and highlight bottlenecks and inefficiencies of existing approaches. Based on our study, we show the need for novel monitoring solutions for the IoT and define a set of requirements.}
    }

BibTex:

    @Article{OJIOT_2021v7i1n08_Rosabal,
        title     = {Massive Wireless Energy Transfer with Multiple Power Beacons for Very Large Internet of Things},
        author    = {Osmel Martinez Rosabal and
                     Onel L. Alcaraz Lopez and
                     Hirley Alves and
                     Richard D. Souza and
                     Samuel Montejo-Sanchez},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2021},
        volume    = {7},
        number    = {1},
        pages     = {83--92},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2021082919333702287224},
        urn       = {urn:nbn:de:101:1-2021082919333702287224},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The Internet of Things (IoT) comprises an increasing number of low-power and low-cost devices that autonomously interact with the surrounding environment. As a consequence of their popularity, future IoT deployments will be massive, which demands energy-efficient systems to extend their lifetime and improve the user experience. Radio frequency wireless energy transfer has the potential of powering massive IoT networks, thus eliminating the need for frequent battery replacement by using the so-called power beacons (PBs). In this paper, we provide a framework for minimizing the sum transmit power of the PBs using devices' positions information and their current battery state. Our strategy aims to reduce the PBs' power consumption and to mitigate the possible impact of the electromagnetic radiation on human health. We also present analytical insights for the case of very distant clusters and evaluate their applicability. Numerical results show that our proposed framework reduces the outage probability as the number of PBs and/or the energy demands increase.}
    }

BibTex:

    @Article{OJIOT_2021v7i1n09_Luz,
        title     = {Network Metrics Detection to Support Internet of Things Application Orchestration},
        author    = {Thamires C. Luz and
                     Cintia B. Margi and
                     Fabio L. Verdi},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2021},
        volume    = {7},
        number    = {1},
        pages     = {93--103},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2021082919334207736575},
        urn       = {urn:nbn:de:101:1-2021082919334207736575},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Software DefinedWireless Sensor Networks (SDWSN) play an important role to serve as an infrastructure to Internet of Things (IoT) applications. In order to improve coverage, reduce costs, and make better use of the available resources, sharing the infrastructure among multiple applications is necessary. Works in the literature aim to enable resource sharing by allocating applications dynamically according to the resources available on the node. However, these works do not monitor if a node stops complying with application requirements once the application is allocated. Thus, network metrics detection is essential to identify nodes that are not able to comply with the application requirements. In this paper, we present the IT-SDN Manager architecture which is composed of a monitoring module and a resource orchestrator. The monitoring module monitors the network metrics, enabling the orchestrator to identify nodes that reach a certain threshold for energy available and packet loss. This threshold configuration depends on the metric characteristics. For packet loss, we present a study showing how it should be defined according to the network size and applications executed in the network. In order to evaluate the orchestrator detection rate, we set two application requirements to identify nodes that reach 90\% of available energy and packet loss greater than the obtained threshold for each scenario studied. Results from the simulations executed show that the resource orchestrator detects all the nodes that reach the available energy threshold, and at least 85\%, with an average of 97\%, of the nodes that reach the packet loss threshold.}
    }

BibTex:

    @Article{OJIOT_2021v7i1n10_Xavier,
        title     = {Data-Centric Edge Federation: A Multi-Edge Architecture for Data Stream Processing of IoT Applications},
        author    = {Tiago C. S. Xavier and
                     Paulo F. Pires and
                     Flavia C. Delicato},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2021},
        volume    = {7},
        number    = {1},
        pages     = {104--115},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2021082919334774324679},
        urn       = {urn:nbn:de:101:1-2021082919334774324679},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Emerging Internet of Things (IoT) applications demand data stream processing with low latency and high processing power. Although the cloud naturally provides huge processing capacity, high latency to move data to the datacenter is prohibitive. Edge computing is a recent paradigm where part of computing and storage resources are pushed from the cloud to the edge of the network. In edge computing, edge providers manage their resources near to IoT devices to meet low latency application requirements and reduce the network core bandwidth. To reach the maximum potential of edge computing, a big challenge is to promote the cooperation between edge providers. Currently, edge computing architectures are severely limited for providing cooperation mechanisms between distinct edge providers. In this paper, we propose a edge federation to leverage the cooperation between different edge providers. The edge federation uses interest information propagated in data streams that travel between edge providers to allow an stakeholder to react to inefficient resource allocation and service provision. The main objective of the federation is to create a consortium of edge providers to provide cooperation mechanisms and define and standardize the application interests. The proposed edge federation is (i) data-centric, since edge providers can share common interests and data and, thus, establish cooperation to increase the capacity to  provide services for applications; (ii) distributed, since no assumption is made concerning the geo-location of the edge providers and their logical connections; (iii) opportunistic, because an edge provider can react dynamically to the environment change ; (iv) scalable, since the edge provider has the ability to analyze a data flow passing by its infrastructure and make decisions to increase network performance locally, which impacts the global performance}
    }

BibTex:

    @Article{OJIOT_2021v7i1n11_Mercan,
        title     = {Building Next Generation IoT Infrastructure for Enabling M2M Crypto Economy},
        author    = {Suat Mercan and
                     Kemal Akkaya},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2021},
        volume    = {7},
        number    = {1},
        pages     = {116--124},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2021082919335284680103},
        urn       = {urn:nbn:de:101:1-2021082919335284680103},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {As Bitcoin and other cryptocurrencies are becoming part of our lives, there is a growing interest to enable using them in our daily lives even for micropayments. This interest stems from many factors including privacy, convenience and overhead/fraud that comes with credit cards. In this regard, Internet of Things (IoT) devices can also benefit from this feature for enabling touchless payments for users. However, there is even a bigger opportunity there considering the nature and diversity of very large-scale unattended IoT devices. The integration of any IoT device with blockchain including cryptocurrencies and smart contracts can trigger a machine-to-machine (M2M) economy revolution by streamlining business among IoT devices. Under such a future business model, IoT devices can autonomously request a service and make a payment in return. Such a large-scale ecosystem should rely on various components thus requiring a paradigm shift on the current design and understanding of the IoT systems. In particular, decentralized architecture of blockchain with cryptocurrency and smart contract capability can be a key enabler. In this vision paper, we advocate the need and necessary elements of a M2M crypto economy infrastructure and investigate the role of blockchain in realizing this vision. We specifically focus on the advantages and challenges of blockchain-based systems along with the existing proposed solutions. We then offer several future directions in creating such a M2M economy.}
    }

BibTex:

    @Article{OJIOT_2021v7i1n12_Karimi,
        title     = {Hierarchical Data Integrity for IoT Devices in Connected Health Applications},
        author    = {Maryam Karimi and
                     Prashant Krishnamurthy},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2021},
        volume    = {7},
        number    = {1},
        pages     = {125--149},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2021102419330607974043},
        urn       = {urn:nbn:de:101:1-2021102419330607974043},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Internet of things devices are increasingly replacing expensive monitoring devices in many environments such as healthcare. People can eventually own their data, collected from smart personal devices, store them in a variety of cloud services, and make them available to service providers of their choice. In such cases, whenever service providers use these data to provide appropriate services, the data owner may become responsible for ensuring the integrity of data retrieved from multiple points. We present a Hierarchical Data Integrity (HDI) approach to verify if the data, sent by monitoring devices to the cloud, remain unchanged. It is hierarchical as follows: there is a quick verification of the integrity of recent health data (in less than 1 ms), followed if necessary by a low overhead secure option for verifying the integrity of both recent and historical data (still only in 6:1 ms). Further, the hierarchy allows granular identification of data units that fail integrity checks, without requiring any key sharing. It is possible for a data owner to periodically (randomly) use a more secure process to verify the integrity of data. This reduces the computation, storage, and time of integrity verification as shown by analysis, simulation, and hardware implementation.}
    }

BibTex:

    @Article{OJIOT_2020v6i1n01e_VLIOT2020,
        title     = {Due to COVID-19 the World's Activities Stopped, but not Research: Workshop on Very Large Internet of Things (VLIoT 2020)},
        author    = {Sven Groppe and
                     Mu-Chun Su},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2020},
        volume    = {6},
        number    = {1},
        pages     = {1--5},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2020080219331432369272},
        urn       = {urn:nbn:de:101:1-2020080219331432369272},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The Very Large Internet of Things (VLIoT) workshop aims at discussing the solutions of problems arising especially for large-scale configurations. After continuously monitoring the global COVID-19 pandemic this year, the workshop changes the format the first time to an online event in order to overcome problems like travel restrictions. Besides missing face-to-face meetings the online format also has chances like an increased number of participants, less travel burdens and saving budget. Hence we received many high-quality submissions, from which we accepted 9 to be introduced in this editorial.}
    }

BibTex:

    @Article{OJIOT_2020v6i1n02_BoMa,
        title     = {Assuring Privacy-Preservation in Mining Medical Text Materials for COVID-19 Cases - A Natural Language Processing Perspective},
        author    = {Bo Ma and
                     Jinsong Wu and
                     Shuang Song and
                     William Liu},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2020},
        volume    = {6},
        number    = {1},
        pages     = {6--13},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2020080219332153513307},
        urn       = {urn:nbn:de:101:1-2020080219332153513307},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Currently, there is a very large volume of Covid-19 related medical data that have been stored in cloud based systems and made available for studing the disease dynamics. without any privacy-preservation. In order to reduce possible privacy leakage and also accommodate massive medical reports with high efficiencies, we proposed a privacypreserving word embody-based text classification method for mining COVID-19 medical documents. It uses the recurrent neural network deep learning algorithm according to the identified internal hiding centralization pattern. In addition, a new model-fusion method is proposed for the continuous improvement of the system performance.The extensive numerical studies have demonstrated that the classifier of the proposed system has superior performance via integrating with the keywords extraction approach. Moreover, the advanced new model does not only accurately capture the keyword patterns but also effectively capture the analogical hierarchy structure of the pathology related datasets with lower computational complexity.}
    }

BibTex:

    @Article{OJIOT_2020v6i1n03_Huu,
        title     = {MASCARA (ModulAr Semantic CAching fRAmework) towards FPGA Acceleration for IoT Security Monitoring},
        author    = {Van Long Nguyen Huu and
                     Julien Lallet and
                     Emmanuel Casseau and
                     Laurent d'Orazio},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2020},
        volume    = {6},
        number    = {1},
        pages     = {14--23},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2020080219332912798426},
        urn       = {urn:nbn:de:101:1-2020080219332912798426},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {With the explosive growth of the Internet Of Things (IOTs), emergency security monitoring becomes essential to efficiently manage an enormous amount of information from heterogeneous systems. In concern of increasing the performance for the sequence of online queries on long-term historical data, query caching with semantic organization, called Semantic Query Caching or Semantic Caching (SC), can play a vital role. SC is implemented mostly in software perspective without providing a generic description of modules or cache services in the given context. Hardware acceleration with FPGA opens new research directions to achieve better performance for SC. Hence, our work aims to propose a flexible, adaptable, and tunable ModulAr Semantic CAching fRAmework (MASCARA) towards FPGA acceleration for fast and accurate massive logs processing applications.}
    }

BibTex:

    @Article{OJIOT_2020v6i1n04_Fuerst,
        title     = {Towards Knowledge Infusion for Robust and Transferable Machine Learning in IoT},
        author    = {Jonathan F{\"u}rst and
                     Mauricio Fadel Argerich and
                     Bin Cheng and
                     Ern{\"o} Kovacs},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2020},
        volume    = {6},
        number    = {1},
        pages     = {24--34},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2020080219333632380804},
        urn       = {urn:nbn:de:101:1-2020080219333632380804},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Machine learning (ML) applications in Internet of Things (IoT) scenarios face the issue that supervision signals, such as labeled data, are scarce and expensive to obtain. For example, it often requires a human to manually label events in a data stream by observing the same events in the real world. In addition, the performance of trained models usually depends on a specific context: (1) location, (2) time and (3) data quality. This context is not static in reality, making it hard to achieve robust and transferable machine learning for IoT systems in practice. In this paper, we address these challenges with an envisioned method that we name Knowledge Infusion. First, we present two past case studies in which we combined external knowledge with traditional data-driven machine learning in IoT scenarios to ease the supervision effort: (1) a weak-supervision approach for the IoT domain to auto-generate labels based on external knowledge (e.g., domain knowledge) encoded in simple labeling functions. Our evaluation for transport mode classification achieves a micro-F1 score of 80.2\%, with only seven labeling functions, on par with a fully supervised model that relies on hand-labeled data. (2) We introduce guiding functions to Reinforcement Learning (RL) to guide the agents' decisions and experience. In initial experiments, our guided reinforcement learning achieves more than three times higher reward in the beginning of its training than an agent with no external knowledge. We use the lessons learned from these experiences to develop our vision of knowledge infusion. In knowledge infusion, we aim to automate the inclusion of knowledge from existing knowledge bases and domain experts to combine it with traditional data-driven machine learning techniques during setup/training phase, but also during the execution phase.}
    }

BibTex:

    @Article{OJIOT_2020v6i1n05_Ruta,
        title     = {Information-Centric Semantic Web of Things},
        author    = {Michele Ruta and
                     Floriano Scioscia},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2020},
        volume    = {6},
        number    = {1},
        pages     = {35--52},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2020080219334321163627},
        urn       = {urn:nbn:de:101:1-2020080219334321163627},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In the Semantic Web of Things (SWoT) paradigm, a plethora of micro-devices permeates an environment. Storage and information processing are decentralized: each component conveys and even processes a (very) small amount of annotated metadata. In this perspective, the node-centric Internet networking model is inadequate. This paper presents a framework for resource discovery in semantic-enhanced pervasive environments leveraging an information-centric networking approach. Information gathered through different Internet of Things (IoT) technologies can be exploited by both ubiquitous and Web-based semantic-aware applications through a uniform set of operations. Experimental results and a case study support sustainability and effectiveness of the proposal.}
    }

BibTex:

    @Article{OJIOT_2020v6i1n06_Heuer,
        title     = {The Internet of Things as a Privacy-Aware Database Machine},
        author    = {Andreas Heuer and
                     Hannes Grunert},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2020},
        volume    = {6},
        number    = {1},
        pages     = {53--65},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2020080219335124583702},
        urn       = {urn:nbn:de:101:1-2020080219335124583702},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Instead of using a computer cluster with homogeneous nodes and very fast high bandwidth connections, we want to present the vision to use the Internet of Things (IoT) as a database machine. This is among others a key factor for smart (assistive) systems in apartments (AAL, ambient assisted living), offices (AAW, ambient assisted working), Smart Cities as well as factories (IIoT, Industry 4.0). It is important to massively distribute the calculation of analysis results on sensor nodes and other low-resource appliances in the environment, not only for reasons of performance, but also for reasons of privacy and protection of corporate knowledge. Thus, functions crucial for assistive systems, such as situation, activity, and intention recognition, are to be automatically transformed not only in database queries, but also in local nodes of lower performance. From a database-specific perspective, analysis operations on large quantities of distributed sensor data, currently based on classical big-data techniques and executed on large, homogeneously equipped parallel computers have to be automatically transformed to billions of processors with energy and capacity restrictions. In this visionary paper, we will focus on the database-specific perspective and the fundamental research questions in the underlying database theory.}
    }

BibTex:

    @Article{OJIOT_2020v6i1n07_Zeuch,
        title     = {NebulaStream: Complex Analytics Beyond the Cloud},
        author    = {Steffen Zeuch and
                     Eleni Tzirita Zacharatou and
                     Shuhao Zhang and
                     Xenofon Chatziliadis and
                     Ankit Chaudhary and
                     Bonaventura Del Monte and
                     Dimitrios Giouroukis and
                     Philipp M. Grulich and
                     Ariane Ziehn and
                     Volker Mark},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2020},
        volume    = {6},
        number    = {1},
        pages     = {66--81},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2020080219335991237696},
        urn       = {urn:nbn:de:101:1-2020080219335991237696},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The arising Internet of Things (IoT) will require significant changes to current stream processing engines (SPEs) to enable large-scale IoT applications. In this paper, we present challenges and opportunities for an IoT data management system to enable complex analytics beyond the cloud. As one of the most important upcoming IoT applications, we focus on the vision of a smart city. The goal of this paper is to bridge the gap between the requirements of upcoming IoT applications and the supported features of an IoT data management system. To this end, we outline how state-of-the-art SPEs have to change to exploit the new capabilities of the IoT and showcase how we tackle IoT challenges in our own system, NebulaStream. This paper lays the foundation for a new type of systems that leverages the IoT to enable large-scale applications over millions of IoT devices in highly dynamic and geo-distributed environments.}
    }

BibTex:

    @Article{OJIOT_2020v6i1n08_Alves,
        title     = {Can You Hear Me? A Metric for Link Asymmetry},
        author    = {Renan C. A. Alves and
                     Cintia B. Margi},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2020},
        volume    = {6},
        number    = {1},
        pages     = {82--88},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2020080219340603524937},
        urn       = {urn:nbn:de:101:1-2020080219340603524937},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The Internet of Things is a networking paradigm aiming to provide computing pervasiveness to our everyday lives. A key component to the Internet of Things is low power networks that gather information from the environment. Low power networks are prone to asymmetric and unidirectional links. Measuring the level of asymmetry and understanding its sources are key steps to successfully deploying sensor networks and the Internet of Things. Our first contribution is a new metric to assess link asymmetry, one which takes into account the instantaneous delivery success probability. Next, we study the influence of four factors on link asymmetry in light of our asymmetry metric, namely, relative distance, output power, relative position, and hardware heterogeneity. With our unique method, we show that all four factors impact link asymmetry.}
    }

BibTex:

    @Article{OJIOT_2020v6i1n09_Neto,
        title     = {An Architecture for Distributed Video Stream Processing in IoMT Systems},
        author    = {Aluizio Rocha Neto and
                     Thiago P. Silva and
                     Thais V. Batista and
                     Flavia C. Delicato and
                     Paulo F. Pires and
                     Frederico Lopes},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2020},
        volume    = {6},
        number    = {1},
        pages     = {89--104},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2020080219341417043601},
        urn       = {urn:nbn:de:101:1-2020080219341417043601},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In Internet of Multimedia Things (IoMT) systems, Internet cameras installed in buildings and streets are major sources of sensing data. From these large-scale video streams, it is possible to infer various information providing the current status of the monitored environments. Some events of interest that have occurred in these observed locations produce insights that might demand near real-time responses from the system. In this context, the event processing depends on data freshness, and computation time, otherwise, the processing results and activities become less valuable or even worthless. An encouraging plan to support the computational demand for latency-sensitive applications of largely geo-distributed systems is applying Edge Computing resources to perform the video stream processing stages. However, some of these stages use deep learning methods for the detection and identification of objects of interest, which are voracious consumers of computational resources. To address these issues, this work proposes an architecture to distribute the video stream processing stages in multiple tasks running on different edge nodes, reducing network overhead and consequent delays. The Multilevel Information Fusion Edge Architecture (MELINDA) encapsulates the data analytics algorithms provided by machine learning methods in different types of processing tasks organized by multiple data-abstraction levels. This distribution strategy, combined with the new category of Edge AI hardware specifically designed to develop smart systems, is a promising approach to address the resource limitations of edge devices.}
    }

BibTex:

    @Article{OJIOT_2020v6i1n10_Ramachandran,
        title     = {ParkingJSON: An Open Standard Format for Parking Data in Smart Cities},
        author    = {Gowri Sankar Ramachandran and
                     Jeremy Stout and
                     Joyce J. Edson and
                     Bhaskar Krishnamachari},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2020},
        volume    = {6},
        number    = {1},
        pages     = {105--118},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2020080219342154738409},
        urn       = {urn:nbn:de:101:1-2020080219342154738409},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Data marketplaces and data management platforms offer a viable solution to build large city-scale Internet of Things (IoT) applications. Contemporary data marketplaces and data management platforms for smart cities such as Intelligent IoT Integrator (I3), Cisco Kinetic, Terbine, and Streamr present a middleware platform to help the data owners to provide their data to the application developers. However, such platforms suffer from adoption issues because of the interoperability concerns that stem from heterogeneous data formats. On the one hand, the IoT devices and the software used by the device owners follow either a custom data standard or a proprietary industrial standard. On the other hand, the application developers consuming data from multiple device owners expect the data to follow one common standard to process the data without developing custom software for each data feed. Therefore, a common data standard is desired to enable interoperable data exchange through data marketplace and data management platforms while promoting adoption. We present our experiences from developing a city-scale real-time parking application for a smart city. We also introduce ParkingJSON, a new open standard format for parking data in smart cities, which could help the parking data providers to cover all types of parking infrastructures through a single JSON schema. To the best of our knowledge, this is the first parking data standard proposed that a) covers a wide range of parking spaces and structures, b) integrates spatial information, and c) provides support for data integrity and authenticity.}
    }

BibTex:

    @Article{OJIOT_2019v5i1n01e_VLIoT2019,
        title     = {Editorial of the 2019 Workshop on Very Large Internet of Things (VLIoT)},
        author    = {Markus Endler and
                     Sven Groppe},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2019},
        volume    = {5},
        number    = {1},
        pages     = {1--5},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2019092919330960165487},
        urn       = {urn:nbn:de:101:1-2019092919330960165487},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {We are proud of presenting the outcome of this third edition of the "Very Large Internet of Things" (VLIoT) workshop, which was held in Los Angeles (USA) in August 2019, in conjunction with the 45th International Conference on Very Large Data Bases (VLDB). Following the success path of the two previous workshop editions - in Munich (2017) and in Rio de Janeiro (2018) - VLIoT 2019 kept its tradition to be a vivid and high-quality technical forum for researchers and practitioners working with Internet of Things to share their experiences, visions and latest findings, most of them regarding the design, implementation, deployment and management of IoT systems at very large and scale. This editorial of the special issue introduces and introduces all papers presented at the workshop.}
    }

BibTex:

    @Article{OJIOT_2019v5i1n02_YiXu,
        title     = {Energy Savings in Very Large Cloud-IoT Systems},
        author    = {Yi Xu and
                     Sumi Helal and
                     Choonhwa Lee and
                     Ahmed Khaled},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2019},
        volume    = {5},
        number    = {1},
        pages     = {6--28},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2019092919332044579216},
        urn       = {urn:nbn:de:101:1-2019092919332044579216},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Opposite to the original cloudlet approach in which an edge is utilized to bring the cloud and its benefits closer to the applications, in cloud- and edge-connected IoT systems where the applications are deployed and run in the cloud, we exploit the edge somewhat differently, either by bringing the physical world and its data up closer to the cloud or by caching parts of the applications down closer to the physical world. Aggressive optimizations seeking substantial IoT energy savings are needed to maintain the scalability of large-scale IoT deployments and to stay within cloud cost constraints (avoiding costly elasticity when working with a budget limit). In this paper, we present a novel optimization approach that relies on the simple principle of minimizing all movements: movements of data from the IoT up to the Edge and Cloud, and movements of application fragments from the cloud down to the edge and the IoT itself. Our approach is novel in that it involves and utilizes the dynamic characteristics and variability of both the data and applications simultaneously. Another novelty of our approach is the definition and use of "sentience-efficiency" as a precursor to "energy-efficiency" for achieving truly aggressive savings in energy. We present our bi-directional optimization approach and its implementation in terms of algorithms within an architecture we name the cloud-edge-beneath architecture (CEB). We present a performance evaluation study to measure the impact of our optimization approach on energy saving.}
    }

BibTex:

    @Article{OJIOT_2019v5i1n03_Santos,
        title     = {Data-Centric Resource Management in Edge-Cloud Systems for the IoT},
        author    = {Igor Le\~{a}o dos Santos and
                     Fl\'{a}via C. Delicato and
                     Paulo F. Pires and
                     Marcelo Pitanga Alves and
                     Ana Oliveira and
                     Tiago Salviano Calmon},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2019},
        volume    = {5},
        number    = {1},
        pages     = {29--46},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2019092919334248197873},
        urn       = {urn:nbn:de:101:1-2019092919334248197873},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {A major challenge in emergent scenarios such as the Cloud-assisted Internet of Things is efficiently managing the resources involved in the system while meeting requirements of applications. From the acquisition of physical data to its transformation into valuable services or information, several steps must be performed, involving the various players in such a complex ecosystem. Support for decentralized data processing on IoT devices and other devices near the edge of the network, in combination with the benefits of cloud technologies has been identified as a promising approach to reduce communication overhead, thus reducing delay for time sensitive IoT applications. The interplay of IoT, edge and cloud to achieve the final goal of producing useful information and value-added services to end user gives rise to a management problem that needs to be wisely tackled. The goal of this work is to propose a novel resource management framework for edge-cloud systems that supports heterogeneity of both devices and application requirements. The framework aims to promote the efficient usage of the system resources while leveraging the Edge Computing features, to meet the low latency requirements of emergent IoT applications. The proposed framework encompasses (i) a lightweight and data-centric virtualization model for edge devices, (ii) a set of components responsible for the resource management and the provisioning of services from the virtualized edge-cloud resources.}
    }

BibTex:

    @Article{OJIOT_2019v5i1n04_Semmler,
        title     = {Online Replication Strategies for Distributed Data Stores},
        author    = {Niklas Semmler and
                     Georgios Smaragdakis and
                     Anja Feldmann},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2019},
        volume    = {5},
        number    = {1},
        pages     = {47--57},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2019092919335387371884},
        urn       = {urn:nbn:de:101:1-2019092919335387371884},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The rate at which data is produced at the network edge, e.g., collected from sensors and Internet of Things (IoT) devices, will soon exceed the storage and processing capabilities of a single system and the capacity of the network. Thus, data will need to be collected and preprocessed in distributed data stores - as part of a distributed database - at the network edge. Yet, even in this setup, the transfer of query results will incur prohibitive costs. To further reduce the data transfers, patterns in the workloads must be exploited. Particularly in IoT scenarios, we expect data access to be highly skewed. Most data will be store-only, while a fraction will be popular. Here, the replication of popular, raw data, as opposed to the shipment of partially redundant query results, can reduce the volume of data transfers over the network. In this paper, we design online strategies to decide between replicating data from data stores or forwarding the queries and retrieving their results. Our insight is that by profiling access patterns of the data we can lower the data transfer cost and the corresponding response times. We evaluate the benefit of our strategies using two real-world datasets.}
    }

BibTex:

    @Article{OJIOT_2019v5i1n05_Segura,
        title     = {Understanding the Performance of Software Defined Wireless Sensor Networks under Denial of Service Attack},
        author    = {Gustavo A. Nunez Segura and
                     Cintia B. Margi and
                     Arsenia Chorti},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2019},
        volume    = {5},
        number    = {1},
        pages     = {58--68},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2019092919340426551900},
        urn       = {urn:nbn:de:101:1-2019092919340426551900},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Wireless sensor networks (WSN) are formed from restricted devices and are known to be vulnerable to denial of service (DoS) security attacks. In parallel, software-defined networking has been identified as a solution for many WSN challenges with respect to flexibility and reuse. Conversely, the SDN control plane centralization may bring about new security threats and vulnerabilities. In this work, we perform a traffic analysis of software-defined WSN (SDWSN) in order to gain understanding of the network's performance when it is under certain types of DoS attacks. In particular, we consider three different DoS scenarios of increasing aggressiveness: (i) false flow requests DoS, (ii) false data flow forwarding DoS, and, (iii) false neighbor information passing DoS. Our simulation results for the latter two types of attack showed significant changes both in the average value and the variance of the delivery rate and the overall overhead. These results demonstrate that it is possible to identify when a SDWSN is under a particular type of DoS, by monitoring the respective quantities.}
    }

BibTex:

    @Article{OJIOT_2019v5i1n06_TaoPeng,
        title     = {IoT Data Imputation with Incremental Multiple Linear Regression},
        author    = {Tao Peng and
                     Sana Sellami and
                     Omar Boucelma},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2019},
        volume    = {5},
        number    = {1},
        pages     = {69--79},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2019092919341561784402},
        urn       = {urn:nbn:de:101:1-2019092919341561784402},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In this paper, we address the problem related to missing data imputation in the IoT domain. More specifically, we propose an Incremental Space-Time-based model (ISTM) for repairing missing values in IoT real-time data streams. ISTM is based on Incremental Multiple Linear Regression, which processes data as follows: Upon data arrival, ISTM updates the model after reading again the intermediary data matrix instead of accessing all historical information. If a missing value is detected, ISTM will provide an estimation for the missing value based on nearly historical data and the observations of neighboring sensors of the default one. Experiments conducted with real traffic data show the performance of ISTM in comparison with known techniques.}
    }

BibTex:

    @Article{OJIOT_2019v5i1n07_Ramachandran,
        title     = {Towards a Large Scale IoT through Partnership, Incentive, and Services: A Vision, Architecture, and Future Directions},
        author    = {Gowri Sankar Ramachandran and
                     Bhaskar Krishnamachari},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2019},
        volume    = {5},
        number    = {1},
        pages     = {80--92},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2019092919345869785889},
        urn       = {urn:nbn:de:101:1-2019092919345869785889},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Internet of Things applications has been deployed and managed in a small to a medium scale deployments in industries and small segments of cities in the last decade. These real-world deployments not only helped the researchers and application developers to create protocols, standards, and frameworks but also helped them understand the challenges associated with the maintenance and management of IoT deployments in all kinds of operational environments. Despite the technological advancements and the deployment experiences, the technology failed to create a notable momentum towards large scale IoT applications involving thousands of IoT devices. We argue the reasons behind the lack of large scale deployments and the limitations of contemporary IoT deployment model. In addition, we present an approach involving multiple stakeholders as a means to scale IoT applications to hundreds of devices. Besides, we argue that the partnership, incentive mechanisms, privacy, and security frameworks are the critical factors for large scale IoT deployments of the future.}
    }

BibTex:

    @Article{OJIOT_2019v5i1n08_Tourani,
        title     = {Distributed Data-Gathering and -Processing in Smart Cities: An Information-Centric Approach},
        author    = {Reza Tourani and
                     Abderrahmen Mtibaa and
                     Satyajayant Misra},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2019},
        volume    = {5},
        number    = {1},
        pages     = {93--104},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2019092919342634548084},
        urn       = {urn:nbn:de:101:1-2019092919342634548084},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The technological advancements along with the proliferation of smart and connected devices (things) motivated the exploration of the creation of smart cities aimed at improving the quality of life, economic growth, and efficient resource utilization. Some recent initiatives defined a smart city network as the interconnection of the existing independent and heterogeneous networks and the infrastructure. However, considering the heterogeneity of the devices, communication technologies, network protocols, and platforms the interoperability of these networks is a challenge requiring more attention. In this paper, we propose the design of a novel Information-Centric Smart City architecture (iSmart), focusing on the demand of the future applications, such as efficient machineto-machine communication, low latency computation offloading, large data communication requirements, and advanced security. In designing iSmart, we use the Named-Data Networking (NDN) architecture as the underlying communication substrate to promote semantics-based communication and achieve seamless compute/data sharing.}
    }

BibTex:

    @Article{OJIOT_2019v5i1n09_Carvalho,
        title     = {Leveraging Application Development for the Internet of Mobile Things},
        author    = {Felipe Carvalho and
                     Markus Endler and
                     Francisco Silva e Silva},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2019},
        volume    = {5},
        number    = {1},
        pages     = {105--116},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2019092919343755312186},
        urn       = {urn:nbn:de:101:1-2019092919343755312186},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {So far, most of research and development for the Internet of Things has been focused at systems where the smart objects, WPAN beacons, sensors, and actuators are mainly stationary and associated with a fixed location (such as appliances in a home or office, an energy meter for a building), and are not capable of handling unrestricted/arbitrary forms of mobility. However, our current lifestyle and economy are increasingly mobile, as people, vehicles, and goods move independently in public and private areas (e.g., automated logistics, retail). Therefore, we are witnessing an increasing need to support Machine to Machine (M2M) communication, data collection, and processing and actuation control for mobile smart things, establishing what is called the Internet of Mobile Things (IoMT). Examples of mobile smart things that fit in the definition of IoMT include Unmanned Aerial Vehicles (UAVs), all sorts of human-crewed vehicles (e.g., cars, buses), and even people with wearable devices such as smart watches or fitness and health monitoring devices. Among these mobile IoT applications, there are several that only require occasional data probes from a mobile sensor, or need to control a smart device only in some specific conditions, or context, such as only when any user is in the ambient. While IoT systems still lack some general programming concepts and abstractions, this is even more so for IoMT. This paper discusses the definition and implementation of suitable programming concepts for mobile smart things - given several examples and scenarios of mobility-specific sensoring and actuation control, both regarding smart things individually, or in terms of collective smart things behaviors. We then show a proposal of programming constructs and language, and show how we will implement an IoMT application programming model, namely OBSACT, on the top of our current middleware ContextNet.}
    }

BibTex:

    @Article{OJIOT_2019v5i1n10_Sotres,
        title     = {Integrating a Smart City Testbed into a Large-Scale Heterogeneous Federation of Future Internet Experimentation Facilities: the SmartSantander Approach},
        author    = {Pablo Sotres and
                     Jorge Lanza and
                     Juan Ram\'{o}n Santana and
                     Luis S\'{a}nchez},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2019},
        volume    = {5},
        number    = {1},
        pages     = {117--132},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2019092919344775371207},
        urn       = {urn:nbn:de:101:1-2019092919344775371207},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {For some years already, there has been a plethora of research initiatives throughout the world that have deployed diverse experimentation facilities for Future Internet technologies research and development. While access to these testbeds has been sometimes restricted to the specific research community supporting them, opening them to different communities can not only help those infrastructures to achieve a wider impact, but also to better identify new possibilities based on novel considerations brought by those external users. On top of the individual testbeds, supporting experiments that employs several of them in a combined and seamless fashion has been one of the main objectives of different transcontinental research initiatives, such as FIRE in Europe or GENI in United States. In particular, Fed4FIRE project and its continuation, Fed4FIRE+, have emerged as "best-in-town" projects to federate heterogeneous experimentation platforms. This paper presents the most relevant aspects of the integration of a large scale testbed on the IoT domain within the Fed4FIRE+ federation. It revolves around the adaptation carried out on the SmartSantander smart city testbed. Additionally, the paper offers an overview of the different federation models that Fed4FIRE+ proposes to testbed owners in order to provide a complete view of the involved technologies. The paper is also presenting a survey of how several specific research platforms from different experimentation domains have fulfilled the federation task following Fed4FIRE+ concepts.}
    }

BibTex:

    @Article{OJIOT_2019v5i1n11_Mauldin,
        title     = {Experimentation and Analysis of Ensemble Deep Learning in IoT Applications},
        author    = {Taylor Mauldin and
                     Anne H. Ngu and
                     Vangelis Metsis and
                     Marc E. Canby and
                     Jelena Tesic},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2019},
        volume    = {5},
        number    = {1},
        pages     = {133--149},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2019092919352344146661},
        urn       = {urn:nbn:de:101:1-2019092919352344146661},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {This paper presents an experimental study of Ensemble Deep Learning (DL) techniques for the analysis of time series data on IoT devices. We have shown in our earlier work that DL demonstrates superior performance compared to traditional machine learning techniques on fall detection applications due to the fact that important features in time series data can be learned and need not be determined manually by the domain expert. However, DL networks generally require large datasets for training. In the health care domain, such as the real-time smartwatch-based fall detection, there are no publicly available large annotated datasets that can be used for training, due to the nature of the problem (i.e. a fall is not a common event). Moreover, fall data is also inherently noisy since motions generated by the wrist-worn smartwatch can be mistaken for a fall. This paper explores combing DL (Recurrent Neural Network) with ensemble techniques (Stacking and AdaBoosting) using a fall detection application as a case study. We conducted a series of experiments using two different datasets of simulated falls for training various ensemble models. Our results show that an ensemble of deep learning models combined by the stacking ensemble technique, outperforms a single deep learning model trained on the same data samples, and thus, may be better suited for small-size datasets.}
    }

BibTex:

    @Article{OJIOT_2019v5i1n12_Misic,
        title     = {Data Lifetime Estimation in a Multicast-Based CoAP Proxy},
        author    = {Jelena Misic and
                     Vojislav B. Misic and
                     Xiaolin Chang},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2019},
        volume    = {5},
        number    = {1},
        pages     = {150--162},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2019092919351017303648},
        urn       = {urn:nbn:de:101:1-2019092919351017303648},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In this work we consider kernel-based record lifetime estimation in a proactive Internet of Things (IoT) proxy with multicast based cache management. Multicast refreshment requests were based on lifetime expiration for a predefined number of records. To reduce the traffic volume in the IoT domain, we assume that only nodes where the observed physical variable has changed its value will respond to the multicast request. For estimating the data lifetime at the proxy, we use Gaussian kernels, assuming that the intrinsic data lifetime probability distribution was taken from Erlang-k family of sub-exponential distributions. In this setup, we consider that the proxy connects to the IoT domain using an IEEE 802.15.4-compatible wireless network. Results indicate that narrow and symmetrical lifetime probability distributions require more frequent multicasting refreshments compared to wider and asymmetric ones. This increases traffic intensity and energy consumption in IoT domain. We quantify finding with numerical results.}
    }

BibTex:

    @Article{OJIOT_2018v4i1n01_VLIoT2018,
        title     = {Editorial of the Workshop on Very Large Internet of Things (VLIoT 2018)},
        author    = {Sven Groppe and
                     Carlo Alberto Boano},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2018},
        volume    = {4},
        number    = {1},
        pages     = {1--6},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2018) in conjunction with the VLDB 2018 Conference in Rio de Janeiro, Brazil.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018080519324071729480},
        urn       = {urn:nbn:de:101:1-2018080519324071729480},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The 2nd "Very Large Internet of Things" (VLIoT) workshop in conjunction with the 44th International Conference on Very Large Data Bases (VLDB) taking place in Rio de Janeiro, Brazil in 2018 is a forum for all researchers in the area of Internet of Things especially interested in related data management issues. This editorial of a special issue containing the workshop's papers provides an overview over the aims and scope of the workshop and the review procedure. Furthermore, we determine and shortly analyze a statistics of the topics addressed by the accepted papers.}
    }

BibTex:

    @Article{OJIOT_2018v4i1n02_Endler,
        title     = {Past, Present and Future of the ContextNet IoMT Middleware},
        author    = {Markus Endler and
                     Francisco Silva e Silva},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2018},
        volume    = {4},
        number    = {1},
        pages     = {7--23},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2018) in conjunction with the VLDB 2018 Conference in Rio de Janeiro, Brazil.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018080519323267622857},
        urn       = {urn:nbn:de:101:1-2018080519323267622857},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The Internet of Things with support to mobility is already transforming many application domains, such as smart cities and homes, environmental monitoring, health care, manufacturing, logistics, public security etc. in that it allows to collect and analyze data from the environment, people and machines, and to implement some form of control or steering on these elements of the physical world. But in order to speed the development of applications for the Internet of Mobile Things (IoMT), some middleware is required. This paper summarizes seven years of research and development on the ContextNet middle ware aimed at IoMT, discusses what we achieved and what we have learned so far. We also share our vision of possible future challenges and developments in the Internet of Mobile Things.}
    }

BibTex:

    @Article{OJIOT_2018v4i1n03_Valim,
        title     = {Middleware Support for Generic Actuation in the Internet of Mobile Things},
        author    = {Sheriton Valim and
                     Matheus Zeitune and
                     Bruno Olivieri and
                     Markus Endler},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2018},
        volume    = {4},
        number    = {1},
        pages     = {24--34},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2018) in conjunction with the VLDB 2018 Conference in Rio de Janeiro, Brazil.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018080519322337232186},
        urn       = {urn:nbn:de:101:1-2018080519322337232186},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {As the Internet of Things is expanding towards applications in almost any sector of our economy and daily life, so is the demand of employing and integrating devices with actuation capabilities, such as smart bulbs, HVAC,smart locks, industrial machines, robots or drones. Many middleware platforms have been developed in orderto support the development of distributed IoT applications and facilitate the sensors-to-cloud communication andedge processing capabilities, but surprisingly very little has been done to provide middleware-level, support andgeneric mechanisms for discovering the devices and their interfaces, and executing the actuation commands, i.e.transferring them to the device. In this paper, we present a generic support for actuation as an extension ofContextNet, our mobile-cloud middleware for IoMT. We describe the design of the distributed actuation supportand present a proof of working implementation that enables remote control of a Sphero mobile BB-8 toy.}
    }

BibTex:

    @Article{OJIOT_2018v4i1n04_Khaled,
        title     = {Service-Relationship Programming Framework for the Social IoT},
        author    = {Ahmed E. Khaled and
                     Wyatt Lindquist and
                     Abdelsalam (Sumi) Helal},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2018},
        volume    = {4},
        number    = {1},
        pages     = {35--53},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2018) in conjunction with the VLDB 2018 Conference in Rio de Janeiro, Brazil.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018080519302286990058},
        urn       = {urn:nbn:de:101:1-2018080519302286990058},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {We argue that for a true realization of innovative programming opportunities for smart spaces, the developers should be equipped with informative tools that assist them in building domain-related applications. Such tools should utilize the services offered by the space's smart things and consider the different relationships that may tie these services opportunistically to build applications. In this paper, we utilize our Inter-thing relationships programming framework to present a distributed programming ecosystem. The framework broadens the restricted set of thing-level relationships of the evolving social IoT paradigm with a set of service-level relationships. Such relationships provide guidance into how services belonging to different things can be combined to build meaningful applications. We also present a uniform way of describing the thing services and the service-level relationships along with new capabilities for the things to dynamically generate their own services, formulate the corresponding programmable interfaces (APIs) and create an ad-hoc network of socially related smart things at runtime. We then present the semantic rules that guide the establishment of IoT applications and finally demonstrate the features of the framework through a proof-of-concept application.}
    }

BibTex:

    @Article{OJIOT_2018v4i1n05_Grunert,
        title     = {Query Rewriting by Contract under Privacy Constraints},
        author    = {Hannes Grunert and
                     Andreas Heuer},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2018},
        volume    = {4},
        number    = {1},
        pages     = {54--69},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2018) in conjunction with the VLDB 2018 Conference in Rio de Janeiro, Brazil.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018080519303109386858},
        urn       = {urn:nbn:de:101:1-2018080519303109386858},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In this paper we show how Query Rewriting rules and Containment checks of aggregate queries can be combined with Contract-based programming techniques. Based on the combination of both worlds, we are able to find new Query Rewriting rules for queries containing aggregate constraints. These rules can either be used to improve the overall system performance or, in our use case, to implement a privacy-aware way to process queries. By integrating them in our PArADISE framework, we can now process and rewrite all types of OLAP queries, including complex aggregate functions and group-by extensions. In our framework, we use the whole network structure, from data producing sensors up to cloud computers, to automatically deploy an edge computing subnetwork. On each edge node, so-called fragment queries of a genuine query are executed to filter and to aggregate data on resource restricted sensor nodes. As a result of integrating Contract-based programming approaches, we are now able to not only process less data but also to produce less data in the result. Thus, the privacy principle of data minimization is accomplished.}
    }

BibTex:

    @Article{OJIOT_2018v4i1n06_Fuerst,
        title     = {Towards Adaptive Actors for Scalable IoT Applications at the Edge},
        author    = {Jonathan F{\"u}rst and
                     Mauricio Fadel Argerich and
                     Kaifei Chen and
                     Ern{\"o} Kovacs},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2018},
        volume    = {4},
        number    = {1},
        pages     = {70--86},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2018) in conjunction with the VLDB 2018 Conference in Rio de Janeiro, Brazil.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018080519303887853107},
        urn       = {urn:nbn:de:101:1-2018080519303887853107},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Traditional device-cloud architectures are not scalable to the size of future IoT deployments. While edge and fog-computing principles seem like a tangible solution, they increase the programming effort of IoT systems, do not provide the same elasticity guarantees as the cloud and are of much greater hardware heterogeneity. Future IoT applications will be highly distributed and place their computational tasks on any combination of end-devices (sensor nodes, smartphones, drones), edge and cloud resources in order to achieve their application goals. These complex distributed systems require a programming model that allows developers to implement their applications in a simple way (i.e., focus on the application logic) and an execution framework that runs these applications resiliently with a high resource efficiency, while maximizing application utility. Towards such distributed execution runtime, we propose Nandu, an actor based system that adapts and migrates tasks dynamically using developer provided hints as seed information. Nandu allows developers to focus on sequential application logic and transforms their application into distributed, adaptive actors. The resulting actors support fine-grained entry points for the execution environment. These entry points allow local schedulers to adapt actors seamlessly to the current context, while optimizing the overall application utility according to developer provided requirements.}
    }

BibTex:

    @Article{OJIOT_2018v4i1n07_Ngu,
        title     = {Smartwatch-Based IoT Fall Detection Application},
        author    = {Anne H. Ngu and
                     Po-Teng Tseng and
                     Manvick Paliwal and
                     Christopher Carpenter and
                     Walker Stipe},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2018},
        volume    = {4},
        number    = {1},
        pages     = {87--98},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2018) in conjunction with the VLDB 2018 Conference in Rio de Janeiro, Brazil.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018080519304951282148},
        urn       = {urn:nbn:de:101:1-2018080519304951282148},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {This paper proposes using only the streaming accelerometer data from a commodity-based smartwatch (IoT) device to detect falls. The smartwatch is paired with a smartphone as a means for performing the computation necessary for the prediction of falls in realtime without incurring latency in communicating with a cloud server while also preserving data privacy. The majority of current fall detection applications require specially designed hardware and software which make them expensive and inaccessible to the general public. Moreover, a fall detection application that uses a wrist worn smartwatch for data collection has the added benefit that it can be perceived as a piece of jewelry and thus non-intrusive. We experimented with both Support Vector Machine and Naive Bayes machine learning algorithms for the creation of the fall model. We demonstrated that by adjusting the sampling frequency of the streaming data, computing acceleration features over a sliding window, and using a Naive Bayes machine learning model, we can obtain the true positive rate of fall detection in real-world setting with 93.33\% accuracy. Our result demonstrated that using a commodity-based smartwatch sensor can yield fall detection results that are competitive with those of custom made expensive sensors.}
    }

BibTex:

    @Article{OJIOT_2018v4i1n08_Margi,
        title     = {Software-Defined Wireless Sensor Networks Approach: Southbound Protocol and Its Performance Evaluation},
        author    = {Cintia B. Margi and
                     Renan C. A. Alves and
                     Gustavo A. Nunez Segura and
                     Doriedson A. G. Oliveira},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2018},
        volume    = {4},
        number    = {1},
        pages     = {99--108},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2018) in conjunction with the VLDB 2018 Conference in Rio de Janeiro, Brazil.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018080519305710189607},
        urn       = {urn:nbn:de:101:1-2018080519305710189607},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Software Defined Networking (SDN) has been identified as a promising network paradigm for Wireless Sensor Networks (WSN) and the Internet of Things. It is a key tool for enabling Sensing as a Service, which provides infrastructure sharing thus reducing operational costs. While a few proposals on SDN southbound protocols designed for WSN are found in the literature, they lack adequate performance analysis. In this paper, we review ITSDN main features and present a performance evaluation with all the sensing nodes transmitting data periodically. We conducted a number of experiments varying the number of nodes and assessing the impact of flow table maximum capacity. We assessed the metrics of data delivery, data delay, control overhead and energy consumption in order to show the tradeoffs of using IT-SDN in comparison to the IETF RPL routing protocol. We discuss the main challenges still faced by IT-SDN in larger WSN, and how they could be addressed to make IT-SDN use worthwhile.}
    }

BibTex:

    @Article{OJIOT_2018v4i1n09_XinLiu,
        title     = {Identifying Malicious Nodes in Multihop IoT Networks using Dual Link Technologies and Unsupervised Learning},
        author    = {Xin Liu and
                     Mai Abdelhakim and
                     Prashant Krishnamurthy and
                     David Tipper},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2018},
        volume    = {4},
        number    = {1},
        pages     = {109--125},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2018) in conjunction with the VLDB 2018 Conference in Rio de Janeiro, Brazil.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018080519310495220214},
        urn       = {urn:nbn:de:101:1-2018080519310495220214},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Packet manipulation attack is one of the challenging threats in cyber-physical systems (CPSs) and Internet of Things (IoT), where information packets are corrupted during transmission by compromised devices. These attacks consume network resources, result in delays in decision making, and could potentially lead to triggering wrong actions that disrupt an overall system's operation. Such malicious attacks as well as unintentional faults are difficult to locate/identify in a large-scale mesh-like multihop network, which is the typical topology suggested by most IoT standards. In this paper, first, we propose a novel network architecture that utilizes powerful nodes that can support two distinct communication link technologies for identification of malicious networked devices (with typical singlelink technology). Such powerful nodes equipped with dual-link technologies can reveal hidden information within meshed connections that is hard to otherwise detect. By applying machine intelligence at the dual-link nodes, malicious networked devices in an IoT network can be accurately identified. Second, we propose two techniques based on unsupervised machine learning, namely hard detection and soft detection, that enable dual-link nodes to identify malicious networked devices. Our techniques exploit network diversity as well as the statistical information computed by dual-link nodes to identify the trustworthiness of resource-constrained devices. Simulation results show that the detection accuracy of our algorithms is superior to the conventional watchdog scheme, where nodes passively listen to neighboring transmissions to detect corrupted packets. The results also show that as the density of the dual-link nodes increases, the detection accuracy improves and the false alarm rate decreases.}
    }

BibTex:

    @Article{OJIOT_2018v4i1n10_Lau,
        title     = {Techniques for the Generation of Arbitrary Three-Dimensional Shapes in Tile-Based Self-Assembly Systems},
        author    = {Florian-Lennert Lau and
                     Kristof Stahl and
                     Stefan Fischer},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2018},
        volume    = {4},
        number    = {1},
        pages     = {126--134},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2018) in conjunction with the VLDB 2018 Conference in Rio de Janeiro, Brazil.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018080519311410579164},
        urn       = {urn:nbn:de:101:1-2018080519311410579164},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {A big challenge in nanorobotics is the construction of nanoscale objects. DNA is a bio-compatible tool to reliably and constructively create objects at the nanoscale. A possible tool to build nano-sized structures are tile-based self-assembly systems on the basis of DNA. It is challenging and time-consuming to efficiently design blueprints for the desired objects. This paper presents basic algorithms for the creation of tilesets for nxnxn-cubes in the aTAM model. Only few publications focus on three-dimensional DNA crystals. Three-dimensional shapes are likely to be of more use in nanorobotics. We present three variations: hollow cubes, cube-grids and filled cubes. The paper also presents a basic algorithm to create arbitrary, finite, connected, three-dimensional and predefined shapes at temperature 1, as well as ideas for more efficient algorithms. Among those are algorithms for spheres, ellipsoids, red blood cells and other promising designs. The algorithms and tilesets are tested/verified using a software that has been developed for the purpose of verifying three-dimensional sets of tiletypes and was influenced by the tool ISU TAS. Others can use the simulator and the algorithms to quickly create sets of tiletypes for their desired nanostructures. A long learning process may thus be omitted.}
    }

BibTex:

    @Article{OJIOT_2018v4i1n11_Ardelt,
        title     = {Towards Intrinsic Molecular Communication Using Isotopic Isomerism},
        author    = {Gunther Ardelt and
                     Christoph K{\"u}lls and
                     Horst Hellbr{\"u}ck},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2018},
        volume    = {4},
        number    = {1},
        pages     = {135--143},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2018) in conjunction with the VLDB 2018 Conference in Rio de Janeiro, Brazil.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018080519312150952526},
        urn       = {urn:nbn:de:101:1-2018080519312150952526},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In this paper we introduce a new approach for molecular communication (MC). The proposed method uses isotopomers as symbols in a communication scenario, and we name this approach isotopic molecular communication (IMC). We propose a modulation scheme based on isotopic isomerism, where symbols are encoded via isotopes in molecules. This can be advantageous in applications where the communication has to be independent from chemical molecular concentration. Application scenarios include nano communications with isotopes in a macroscopic environment, i.e. encoding freshwater flow of rivers or drinking water utilities, or medical applications where blood carries isotopomers used for communication in a human or animal body. We simulate the capacity of communication in the sense of symbols per second and maximum symbol rate for different applications. We provide estimations for the symbol rate per distance and we demonstrate the feasibility to identify isotopes reliably. In summary, this isotopic molecular communication is a new paradigm for data transfer independent from molecular concentrations and chemical reactions, and can provide higher throughput than ordinary molecular communications.}
    }

BibTex:

    @Article{OJIOT_2018v4i1n12_Miladinovic,
        title     = {Dynamic Allocation of Smart City Applications},
        author    = {Igor Miladinovic and
                     Sigrid Schefer-Wenzl},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2018},
        volume    = {4},
        number    = {1},
        pages     = {144--149},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2018) in conjunction with the VLDB 2018 Conference in Rio de Janeiro, Brazil.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018080519320192483088},
        urn       = {urn:nbn:de:101:1-2018080519320192483088},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Cities around the world are evaluating the potential of Internet of Things (IoT) to automate and optimize public services. Cities that implement this approach are commonly referred to as smart cities. A smart city IoT architecture needs to be layered and scalable in order to fulfill not only today's but also future needs of smart cities. Network Function Virtualization (NFV) provides the scale and flexibility necessary for smart city services by enabling the automated control, management and orchestration of network resources. In this paper we consider a scalable, layered, NFV based smart city architecture and discuss the optimal location of applications regarding cloud computing and mobile edge computing (MEC). Introducing a novel concept of dynamic application allocation we show how to fully benefit from MEC and present relevant decision criteria.}
    }

BibTex:

    @Article{OJIOT_2018v4i1n13_Orazio,
        title     = {Semantic Caching Framework: An FPGA-Based Application for IoT Security Monitoring},
        author    = {Laurent d'Orazio and
                     Julien Lallet},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2018},
        volume    = {4},
        number    = {1},
        pages     = {150--157},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2018) in conjunction with the VLDB 2018 Conference in Rio de Janeiro, Brazil.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2018080519321445601568},
        urn       = {urn:nbn:de:101:1-2018080519321445601568},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Security monitoring is one subdomain of cybersecurity which aims to guarantee the safety of systems, continuously monitoring unusual events. The development of Internet Of Things leads to huge amounts of information, being heterogeneous and requiring to be efficiently managed. Cloud Computing provides software and hardware resources for large scale data management. However, performances for sequences of on-line queries on long term historical data may be not compatible with the emergency security monitoring. This work aims to address this problem by proposing a semantic caching framework and its application to acceleration hardware with FPGA for fast- and accurate-enough logs processing for various data stores and execution engines.}
    }

BibTex:

    @Article{OJIOT_2017v3i1n01_Vossen,
        title     = {A Classification Framework for Beacon Applications},
        author    = {Gottfried Vossen and
                     Stuart Dillon and
                     Fabian Schomm and
                     Florian Stahl},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2017},
        volume    = {3},
        number    = {1},
        pages     = {1--11},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201704245012},
        urn       = {urn:nbn:de:101:1-201704245012},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Beacons have received considerable attention in recent years, which is partially due to the fact that they serve as a flexible and versatile replacement for RFIDs in many applications. However, beacons are mostly considered from a purely technical perspective. This paper provides a conceptual view on application scenarios for beacons and introduces a novel framework for characterizing these. The framework consists of four dimensions: device movement, action trigger, purpose type, and connectivity requirements. Based on these, three archetypical scenarios are described. Finally, event-condition-action rules and online algorithms are used to formalize the backend of a beacon architecture.}
    }

BibTex:

    @Article{OJIOT_2017v3i1n02e_VLIoT2017,
        title     = {First Edition of the Very Large Internet of Things Workshop (VLIoT)},
        author    = {Sven Groppe and
                     Carlo Alberto Boano},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2017},
        volume    = {3},
        number    = {1},
        pages     = {12--17},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with the VLDB 2017 Conference in Munich, Germany.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017080613397},
        urn       = {urn:nbn:de:101:1-2017080613397},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {This article is an editorial for the proceedings of the "Very Large Internet of Things (VLIoT 2017)" workshop in conjunction with the 43th International Conference on Very Large Data Bases (VLDB 2017), which takes place in Munich, Germany, from August 28th to September 1, 2017. The editorial of VLIoT@VLDB 2017 provides an overview over the aims and scope of the workshop, the review procedure, and the accepted papers. The proceedings of VLIoT@VLDB 2017 are published as special issue in the Open Journal of Internet of Things (OJIOT) (www.ronpub.com/ojiot), and the publisher of OJIOT is RonPub (www.ronpub.com).}
    }

BibTex:

    @Article{OJIOT_2017v3i1n03_Balasubramanian,
        title     = {Latency Optimization in Large-Scale Cloud-Sensor Systems},
        author    = {Adhithya Balasubramanian and
                     Sumi Helal and
                     Yi Xu},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2017},
        volume    = {3},
        number    = {1},
        pages     = {18--30},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with the VLDB 2017 Conference in Munich, Germany.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017080613410},
        urn       = {urn:nbn:de:101:1-2017080613410},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {With the advent of the Internet of Things and smart city applications, massive cyber-physical interactions between the applications hosted in the cloud and a huge number of external physical sensors and devices is an inevitable situation. This raises two main challenges: cloud cost affordability as the smart city grows (referred to as economical cloud scalability) and the energy-efficient operation of sensor hardware. We have developed Cloud-Edge-Beneath (CEB), a multi-tier architecture for large-scale IoT deployments, embodying distributed optimizations, which address these two major challenges. In this article, we summarize our prior work on CEB to set context for presenting a third major challenge for cloud sensor-systems, which is latency. Prolonged latency can potentially arise in servicing requests from cloud applications, especially given our primary focus on optimizing energy and cloud scalability. Latency, however, is an important factor to optimize for real-time and cyber-physical applications with limited tolerance to delays. Also, improving the responsiveness of any IoT application is bound to improve the user experience and hence the acceptability and adoption of smart city solutions by the city citizens. In this article, we aim to give a formal definition and formulation for the latency optimization problem under CEB. We propose a Prioritized Application Fragment Caching Algorithm (PAFCA) to selectively cache application fragments from the cloud to lower layers of CEB, as a key measure to optimize latency. The algorithm itself is an extension of one of the existing optimization algorithms of CEB (AFCA-1). As will be shown, PAFCA takes into account the expectations of cloud applications on real-timeliness of responses. Through experiments, we measure and validate the effect of PAFCA on latency and cloud scalability. We also introduce and discuss the trade-off between latency and sensor energy in this given context.}
    }

BibTex:

    @Article{OJIOT_2017v3i1n04_Grunert,
        title     = {Rewriting Complex Queries from Cloud to Fog under Capability Constraints to Protect the Users' Privacy},
        author    = {Hannes Grunert and
                     Andreas Heuer},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2017},
        volume    = {3},
        number    = {1},
        pages     = {31--45},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with the VLDB 2017 Conference in Munich, Germany.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017080613421},
        urn       = {urn:nbn:de:101:1-2017080613421},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In this paper we show how existing query rewriting and query containment techniques can be used to achieve an efficient and privacy-aware processing of queries. To achieve this, the whole network structure, from data producing sensors up to cloud computers, is utilized to create a database machine consisting of billions of devices from the Internet of Things. Based on previous research in the field of database theory, especially query rewriting, we present a concept to split a query into fragment and remainder queries. Fragment queries can operate on resource limited devices to filter and preaggregate data. Remainder queries take these data and execute the last, complex part of the original queries on more powerful devices. As a result, less data is processed and forwarded in the network and the privacy principle of data minimization is accomplished.}
    }

BibTex:

    @Article{OJIOT_2017v3i1n05_Ruta,
        title     = {Semantic Blockchain to Improve Scalability in the Internet of Things},
        author    = {Michele Ruta and
                     Floriano Scioscia and
                     Saverio Ieva and
                     Giovanna Capurso and
                     Eugenio Di Sciascio},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2017},
        volume    = {3},
        number    = {1},
        pages     = {46--61},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with the VLDB 2017 Conference in Munich, Germany.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017080613488},
        urn       = {urn:nbn:de:101:1-2017080613488},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Generally scarce computational and memory resource availability is a well known problem for the IoT, whose intrinsic volatility makes complex applications unfeasible. Noteworthy efforts in overcoming unpredictability (particularly in case of large dimensions) are the ones integrating Knowledge Representation technologies to build the so-called Semantic Web of Things (SWoT). In spite of allowed advanced discovery features, transactions in the SWoT still suffer from not viable trust management strategies. Given its intrinsic characteristics, blockchain technology appears as interesting from this perspective: a semantic resource/service discovery layer built upon a basic blockchain infrastructure gains a consensus validation. This paper proposes a novel Service-Oriented Architecture (SOA) based on a semantic blockchain for registration, discovery, selection and payment. Such operations are implemented as smart contracts, allowing distributed execution and trust. Reported experiments early assess the sustainability of the proposal.}
    }

BibTex:

    @Article{OJIOT_2017v3i1n06_Hegedus,
        title     = {Differentially Private Linear Models for Gossip Learning through Data Perturbation},
        author    = {Istv\'{a}n Hegedus and
                     M\'{a}rk Jelasity},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2017},
        volume    = {3},
        number    = {1},
        pages     = {62--74},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with the VLDB 2017 Conference in Munich, Germany.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017080613445},
        urn       = {urn:nbn:de:101:1-2017080613445},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Privacy is a key concern in many distributed systems that are rich in personal data such as networks of smart meters or smartphones. Decentralizing the processing of personal data in such systems is a promising first step towards achieving privacy through avoiding the collection of data altogether. However, decentralization in itself is not enough: Additional guarantees such as differential privacy are highly desirable. Here, we focus on stochastic gradient descent (SGD), a popular approach to implement distributed learning. Our goal is to design differentially private variants of SGD to be applied in gossip learning, a decentralized learning framework. Known approaches that are suitable for our scenario focus on protecting the gradient that is being computed in each iteration of SGD. This has the drawback that each data point can be accessed only a small number of times. We propose a solution in which we effectively publish the entire database in a differentially private way so that linear learners could be run that are allowed to access any (perturbed) data point any number of times. This flexibility is very useful when using the method in combination with distributed learning environments. We show empirically that the performance of the obtained model is comparable to that of previous gradient-based approaches and it is even superior in certain scenarios.}
    }

BibTex:

    @Article{OJIOT_2017v3i1n07_Ali,
        title     = {Multi-Layer Cross Domain Reasoning over Distributed Autonomous IoT Applications},
        author    = {Muhammad Intizar Ali and
                     Pankesh Patel and
                     Soumya Kanti Datta and
                     Amelie Gyrard},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2017},
        volume    = {3},
        number    = {1},
        pages     = {75--90},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with the VLDB 2017 Conference in Munich, Germany.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017080613451},
        urn       = {urn:nbn:de:101:1-2017080613451},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Due to the rapid advancements in the sensor technologies and IoT, we are witnessing a rapid growth in the use of sensors and relevant IoT applications. A very large number of sensors and IoT devices are in place in our surroundings which keep sensing dynamic contextual information. A true potential of the wide-spread of IoT devices can only be realized by designing and deploying a large number of smart IoT applications which can provide insights on the data collected from IoT devices and support decision making by converting raw sensor data into actionable knowledge. However, the process of getting value from sensor data streams and converting these raw sensor values into actionable knowledge requires extensive efforts from IoT application developers and domain experts. In this paper, our main aim is to propose a multi-layer cross domain reasoning framework, which can support application developers, end-users and domain experts to automatically understand relevant events and extract actionable knowledge with minimal efforts. Our framework reduces the efforts required for IoT applications development (i) by supporting automated application code generation and access mechanisms using IoTSuite, (ii) by leveraging from Machine-to-Machine Measurement (M3) framework to exploit semantic technologies and domain knowledge, and (iii) by using automated sensor discovery and complex event processing of relevant events (ACEIS Middleware) at the multiple data processing layers and different stages of the IoT application development life cycle. In the essence, our framework supports the end-users and IoT application developers to design innovative IoT applications by reducing the programming efforts, by identifying relevant events and by suggesting potential actions based on complex event processing and reasoning for cross-domain IoT applications.}
    }

BibTex:

    @Article{OJIOT_2017v3i1n08_Margi,
        title     = {Sensing as a Service: Secure Wireless Sensor Network Infrastructure Sharing for the Internet of Things},
        author    = {Cintia B. Margi and
                     Renan C. A. Alves and
                     Johanna Sepulveda},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2017},
        volume    = {3},
        number    = {1},
        pages     = {91--102},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with the VLDB 2017 Conference in Munich, Germany.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017080613467},
        urn       = {urn:nbn:de:101:1-2017080613467},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Internet of Things (IoT) andWireless Sensor Networks (WSN) are composed of devices capable of sensing/actuation, communication and processing. They are valuable technology for the development of applications in several areas, such as environmental, industrial and urban monitoring and processes controlling. Given the challenges of different protocols and technologies used for communication, resource constrained devices nature, high connectivity and security requirements for the applications, the main challenges that need to be addressed include: secure communication between IoT devices, network resource management and the protected implementation of the security mechanisms. In this paper, we present a secure Software-Defined Networking (SDN) based framework that includes: communication protocols, node task programming middleware, communication and computation resource management features and security services. The communication layer for the constrained devices considers IT-SDN as its basis. Concerning security, we address the main services, the type of algorithms to achieve them, and why their secure implementation is needed. Lastly, we showcase how the Sensing as a Service paradigm could enable WSN usage in more environments.}
    }

BibTex:

    @Article{OJIOT_2017v3i1n09_Sparber,
        title     = {Mitigating Radio Interference in Large IoT Networks through Dynamic CCA Adjustment},
        author    = {Tommy Sparber and
                     Carlo Alberto Boano and
                     Salil S. Kanhere and
                     Kay R{\"o}mer},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2017},
        volume    = {3},
        number    = {1},
        pages     = {103--113},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with the VLDB 2017 Conference in Munich, Germany.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017080613511},
        urn       = {urn:nbn:de:101:1-2017080613511},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The performance of low-power wireless sensor networks used to build Internet of Things applications often suffers from radio interference generated by co-located wireless devices or from jammers maliciously placed in their proximity. As IoT devices typically operate in unsupervised large-scale installations, and as radio interference is typically localized and hence affects only a portion of the nodes in the network, it is important to give low-power wireless sensors and actuators the ability to autonomously mitigate the impact of surrounding interference. In this paper we present our approach DynCCA, which dynamically adapts the clear channel assessment threshold of IoT devices to minimize the impact of malicious or unintentional interference on both network reliability and energy efficiency. First, we describe how varying the clear channel assessment threshold at run-time using only information computed locally can help to minimize the impact of unintentional interference from surrounding devices and to escape jamming attacks. We then present the design and implementation of DynCCA on top of ContikiMAC and evaluate its performance on wireless sensor nodes equipped with IEEE 802.15.4 radios. Our experimental investigation shows that the use of DynCCA in dense IoT networks can increase the packet reception rate by up to 50\% and reduce the energy consumption by a factor of 4.}
    }

BibTex:

    @Article{OJIOT_2017v3i1n10_Zadorozhny,
        title     = {Data Credence in IoT: Vision and Challenges},
        author    = {Vladimir I. Zadorozhny and
                     Prashant Krishnamurthy and
                     Mai Abdelhakim and
                     Konstantinos Pelechrinis and
                     Jiawei Xu},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2017},
        volume    = {3},
        number    = {1},
        pages     = {114--126},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with the VLDB 2017 Conference in Munich, Germany.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017080613498},
        urn       = {urn:nbn:de:101:1-2017080613498},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {As the Internet of Things permeates every aspect of human life, assessing the credence or integrity of the data generated by "things" becomes a central exercise for making decisions or in auditing events. In this paper, we present a vision of this exercise that includes the notion of data credence, assessing data credence in an efficient manner, and the use of technologies that are on the horizon for the very large scale Internet of Things.}
    }

BibTex:

    @Article{OJIOT_2017v3i1n11_Miladinovic,
        title     = {A Highly Scalable IoT Architecture through Network Function Virtualization},
        author    = {Igor Miladinovic and
                     Sigrid Schefer-Wenzl},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2017},
        volume    = {3},
        number    = {1},
        pages     = {127--135},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with the VLDB 2017 Conference in Munich, Germany.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017080613543},
        urn       = {urn:nbn:de:101:1-2017080613543},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {As the number of devices for Internet of Things (IoT) is rapidly growing, existing communication infrastructures are forced to continually evolve. The next generation network infrastructure is expected to be virtualized and able to integrate different kinds of information technology resources. Network Functions Virtualization (NFV) is one of the leading concepts facilitating the operation of network services in a scalable manner. In this paper, we present an architecture involving NFV to meet the requirements of highly scalable IoT scenarios. We highlight the benefits and challenges of our approach for IoT stakeholders. Finally, the paper illustrates our vision of how the proposed architecture can be applied in the context of a state-of-the-art high-tech operating room, which we are going to realize in future work.}
    }

BibTex:

    @Article{OJIOT_2017v3i1n12_Kross,
        title     = {Towards a Model-driven Performance Prediction Approach for Internet of Things Architectures},
        author    = {Johannes Kro{\ss} and
                     Sebastian Voss and
                     Helmut Krcmar},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2017},
        volume    = {3},
        number    = {1},
        pages     = {136--141},
        note      = {Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with the VLDB 2017 Conference in Munich, Germany.},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-2017080613524},
        urn       = {urn:nbn:de:101:1-2017080613524},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Indisputable, security and interoperability play major concerns in Internet of Things (IoT) architectures and applications. In this paper, however, we emphasize the role and importance of performance and scalability as additional, crucial aspects in planning and building sustainable IoT solutions. IoT architectures are complicated system-of-systems that include different developer roles, development processes, organizational units, and a multilateral governance. Its performance is often neglected during development but becomes a major concern at the end of development and results in supplemental efforts, costs, and refactoring. It should not be relied on linearly scaling for such systems only by using up-to-date technologies that may promote such behavior. Furthermore, different security or interoperability choices also have a considerable impact on performance and may result in unforeseen trade-offs. Therefore, we propose and pursue the vision of a model-driven approach to predict and evaluate the performance of IoT architectures early in the system lifecylce in order to guarantee efficient and scalable systems reaching from sensors to business applications.}
    }

BibTex:

    @Article{OJIOT_2016v2i1n02_Yamaguchi,
        title     = {A 24 GHz FM-CW Radar System for Detecting Closed Multiple Targets and Its Applications in Actual Scenes},
        author    = {Kazuhiro Yamaguchi and
                     Mitumasa Saito and
                     Takuya Akiyama and
                     Tomohiro Kobayashi and
                     Naoki Ginoza and
                     Hideaki Matsue},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2016},
        volume    = {2},
        number    = {1},
        pages     = {1--15},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201704245003},
        urn       = {urn:nbn:de:101:1-201704245003},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {This paper develops a 24 GHz band FM-CW radar system to detect closed multiple targets in a small displacement environment, and its performance is analyzed by computer simulation. The FM-CW radar system uses a differential detection method for removing any signals from background objects and uses a tunable FIR filtering in signal processing for detecting multiple targets. The differential detection method enables the correct detection of both the distance and small displacement at the same time for each target at the FM-CW radar according to the received signals. The basic performance of the FM-CW radar system is analyzed by computer simulation, and the distance and small displacement of a single target are measured in field experiments. The computer simulations are carried out for evaluating the proposed detection method with tunable FIR filtering for the FM-CW radar and for analyzing the performance according to the parameters in a closed multiple targets environment. The results of simulation show that our 24 GHz band FM-CW radar with the proposed detection method can effectively detect both the distance and the small displacement for each target in multiple moving targets environments. Moreover, we develop an IoT-based application for monitoring several targets at the same time in actual scenes.}
    }

BibTex:

    @Article{OJIOT-2016v2i1n02_Aubonnet,
        title     = {Controlled Components for Internet of Things As-A-Service},
        author    = {Tatiana Aubonnet and
                     Amina Boubendir and
                     Fr\'{e}d\'{e}ric Lemoine and
                     N{\"o}emie Simoni},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2016},
        volume    = {2},
        number    = {1},
        pages     = {16--33},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201704244995},
        urn       = {urn:nbn:de:101:1-201704244995},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In order to facilitate developers willing to create future Internet of Things (IoT) services incorporating the nonfunctional aspects, we introduce an approach and an environment based on controlled components. Our approach allows developers to design an IoT "as-a-service", to build the service composition and to manage it. This is important, because the IoT allows us to observe and understand the real world in order to have decision-making information to act on reality. It is important to make sure that all these components work according to their mission, i.e. their Quality of Service (QoS) contract. Our environment provides the modeling, generates Architecture Description Language (ADL) formats, and uses them in the implementation phase on an open-source platform.}
    }

BibTex:

    @Article{OJIOT_2015v1i2n02_Gaur,
        title     = {Evidential Sensor Data Fusion in a Smart City Environment},
        author    = {Aditya Gaur and
                     Bryan W. Scotney and
                     Gerard P. Parr and
                     Sally I. McClean},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2015},
        volume    = {1},
        number    = {2},
        pages     = {1--18},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201704244969},
        urn       = {urn:nbn:de:101:1-201704244969},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Wireless sensor networks have increasingly become contributors of very large amounts of data. The recent deployment of wireless sensor networks in Smart City infrastructures have led to very large amounts of data being generated each day across a variety of domains, with applications including environmental monitoring, healthcare monitoring and transport monitoring. The information generated through the wireless sensor nodes has made possible the visualization of a Smart City environment for better living. The Smart City offers intelligent infrastructure and cogitative environment for the elderly and other people living in the Smart society. Different types of sensors are present that help in monitoring inhabitants' behaviour and their interaction with real world objects. To take advantage of the increasing amounts of data, there is a need for new methods and techniques for effective data management and analysis, to generate information that can assist in managing the resources intelligently and dynamically. Through this research a Smart City ontology model is proposed, which addresses the fusion process related to uncertain sensor data using semantic web technologies and Dempster-Shafer uncertainty theory. Based on the information handling methods, such as Dempster-Shafer theory (DST), an equally weighted sum operator and maximization operation, a higher level of contextual information is inferred from the low-level sensor data fusion process. In addition, the proposed ontology model helps in learning new rules that can be used in defining new knowledge in the Smart City system.}
    }

BibTex:

    @Article{OJIOT_2015v1i2n03_Cho,
        title     = {Accurate Distance Estimation between Things: A Self-correcting Approach},
        author    = {Ho-sik Cho and
                     Jianxun Ji and
                     Zili Chen and
                     Hyuncheol Park and
                     Wonsuk Lee},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2015},
        volume    = {1},
        number    = {2},
        pages     = {19--27},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201704244959},
        urn       = {urn:nbn:de:101:1-201704244959},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {This paper suggests a method to measure the physical distance between an IoT device (a Thing) and a mobile device (also a Thing) using BLE (Bluetooth Low-Energy profile) interfaces with smaller distance errors. BLE is a well-known technology for the low-power connectivity and suitable for IoT devices as well as for the proximity with the range of several meters. Apple has already adopted the technique and enhanced it to provide subdivided proximity range levels. However, as it is also a variation of RSS-based distance estimation, Apple's iBeacon could only provide immediate, near or far status but not a real and accurate distance. To provide more accurate distance using BLE, this paper introduces additional self-correcting beacon to calibrate the reference distance and mitigate errors from environmental factors. By adopting self-correcting beacon for measuring the distance, the average distance error shows less than 10\% within the range of 1.5 meters. Some considerations are presented to extend the range to be able to get more accurate distances.}
    }

BibTex:

    @Article{OJIOT_2015v1i1n02_Syarifah,
        title     = {Modelling the Integrated QoS for Wireless Sensor Networks with Heterogeneous Data Traffic},
        author    = {Syarifah Ezdiani and
                     Adnan Al-Anbuky},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2015},
        volume    = {1},
        number    = {1},
        pages     = {1--15},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201704244946},
        urn       = {urn:nbn:de:101:1-201704244946},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The future of Internet of Things (IoT) is envisaged to consist of a high amount of wireless resource-constrained devices connected to the Internet. Moreover, a lot of novel real-world services offered by IoT devices are realized by wireless sensor networks (WSNs). Integrating WSN to the Internet has therefore brought forward the requirements of an end-to-end quality of service (QoS) guarantee. In this paper, the QoS requirements for the WSN-Internet integration are investigated by first distinguishing the Internet QoS from the WSN QoS. Next, this study emphasizes on WSN applications that involve traffic with different levels of importance, thus the way realtime traffic and delay-tolerant traffic are handled to guarantee QoS in the network is studied. Additionally, an overview of the integration strategies is given, and the delay-tolerant network (DTN) gateway, being one of the desirable approaches for integrating WSNs to the Internet, is discussed. Next, the implementation of the service model is presented, by considering both traffic prioritization and service differentiation. Based on the simulation results in OPNET Modeler, it is observed that real-time traffic achieve low bound delay while delay-tolerant traffic experience a lower packet dropped, hence indicating that the needs of real-time and delay-tolerant traffic can be better met by treating both packet types differently. Furthermore, a vehicular network is used as an example case to describe the applicability of the framework in a real IoT application environment, followed by a discussion on the future work of this research.}
    }

BibTex:

    @Article{OJIOT_2015v1i1n03_Rosa,
        title     = {The Potential of Printed Electronics and Personal Fabrication in Driving the Internet of Things},
        author    = {Paulo Rosa and
                     Ant\'{o}nio C\^{a}mara and
                     Cristina Gouveia},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2015},
        volume    = {1},
        number    = {1},
        pages     = {16--36},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201704244933},
        urn       = {urn:nbn:de:101:1-201704244933},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {In the early nineties, Mark Weiser, a chief scientist at the Xerox Palo Alto Research Center (PARC), wrote a series of seminal papers that introduced the concept of Ubiquitous Computing. Within this vision, computers and others digital technologies are integrated seamlessly into everyday objects and activities, hidden from our senses whenever not used or needed. An important facet of this vision is the interconnectivity of the various physical devices, which creates an Internet of Things. With the advent of Printed Electronics, new ways to link the physical and digital worlds became available. Common printing technologies, such as screen, flexography, and inkjet printing, are now starting to be used not only to mass-produce extremely thin, flexible and cost effective electronic circuits, but also to introduce electronic functionality into objects where it was previously unavailable. In turn, the growing accessibility to Personal Fabrication tools is leading to the democratization of the creation of technology by enabling end-users to design and produce their own material goods according to their needs. This paper presents a survey of commonly used technologies and foreseen applications in the field of Printed Electronics and Personal Fabrication, with emphasis on the potential to drive the Internet of Things.}
    }