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.}
    }