http://www.ronpub.com/index.php/journals/OJCC/issues?volume=1&issue=ALL All papers of this volume en-us https://www.ronpub.com/ojcc/OJCC-v1i2n01_Groppe.html http://nbn-resolving.de/urn:nbn:de:101:1-201705194478 Clouds are dynamic networks of common, off-the-shell computers to build computation farms. The rapid growth of databases in the context of the semantic web requires efficient ways to store and process this data. Using cloud technology for storing and processing Semantic Web data is an obvious way to overcome difficulties in storing and processing the enormously large present and future datasets of the Semantic Web. This paper presents a new approach for storing Semantic Web data, such that operations for the evaluation of Semantic Web queries are more likely to be processed only on local data, instead of using costly distributed operations. An experimental evaluation demonstrates the performance improvements in comparison to a naive distribution of Semantic Web data. https://www.ronpub.com/ojcc/OJCC-2014v1i2n02_Alwabel.html http://nbn-resolving.de/urn:nbn:de:101:1-201705194435 Cloud has emerged as a new computing paradigm that promises to move into computing-as-utility era. Desktop Cloud is a new type of Cloud computing introduced to further achieve this ambition with an aim to reduce costs. It merges two computing models: Cloud computing and volunteer computing. The aim of Desktop Cloud is to provide Cloud services out of infrastructure that is not made for this purpose, like PCs and laptops. Such computing resources lead to a high level of volatility as a result of the fact that they can leave without prior knowledge. This paper studies the impact of node failures using evaluation metrics based on real data collected from public archive to simulate failure events in the infrastructure of a Desktop Cloud. The contribution of this paper is: (i) analysing the failure events, (ii) proposing metrics to evaluate Desktop Clouds, and (iii) evaluating several VM allocation mechanisms in the presence of node failures. https://www.ronpub.com/ojcc/OJCC-v1i1n01_Chang.html http://nbn-resolving.de/urn:nbn:de:101:1-201705194429 This paper introduces the Risk Visualization as a Service (RVaaS) and presents the motivation, rationale, methodology, Cloud APIs used, operations and examples of using RVaaS. Risks can be calculated within seconds and presented in the form of Visualization to ensure that unexploited areas are ex-posed. RVaaS operates in two phases. The first phase includes the risk modeling in Black Scholes Model (BSM), creating 3D Visualization and Analysis. The second phase consists of calculating key derivatives such as Delta and Theta for financial modeling. Risks presented in visualization allow the potential investors and stakeholders to keep track of the status of risk with regard to time, prices and volatility. Our approach can improve accuracy and performance. Results in experiments show that RVaaS can perform up to 500,000 simulations and complete all simulations within 24 seconds for time steps of up to 50. We also introduce financial stock market analysis (FSMA) that can fully blend with RVaaS and demonstrate two examples that can help investors make better decision based on the pricing and market volatility information. RVaaS provides a structured way to deploy low cost, high quality risk assessment and support real-time calculations. https://www.ronpub.com/ojcc/OJCC-v1i1n02_Puzio.html http://nbn-resolving.de/urn:nbn:de:101:1-201705194448 Deduplication is a storage saving technique which has been adopted by many cloud storage providers such as Dropbox. The simple principle of deduplication is that duplicate data uploaded by different users are stored only once. Unfortunately, deduplication is not compatible with encryption. As a scheme that allows deduplication of encrypted data segments, we propose ClouDedup, a secure and efficient storage service which guarantees blocklevel deduplication and data confidentiality at the same time. ClouDedup strengthens convergent encryption by employing a component that implements an additional encryption operation and an access control mechanism. We also propose to introduce an additional component which is in charge of providing a key management system for data blocks together with the actual deduplication operation. We show that the overhead introduced by these new components is minimal and does not impact the overall storage and computational costs. https://www.ronpub.com/ojcc/OJCC-v1i1n03_Chang.html http://nbn-resolving.de/urn:nbn:de:101:1-201705194450 This paper presents the customer satisfaction analysis for measuring popularity in the Mobile Cloud, which is an emerging area in the Cloud and Big Data Computing. Organizational Sustainability Modeling (OSM) is the proposed method used in this research. The twelve-month of German and Spanish consumer data are used for the analysis to investigate the return and risk status associated with the ratings of customer satisfaction in the iPhone 4S Mobile Cloud services. Results show that there is a decline in the satisfaction ratings in Germany and Spain due to economic downturn and competitions in the market, which support our hypothesis. Key outputs have been explained and they confirm that all analysis and interpretations fulfill the criteria for OSM. The use of statistical and visualization method proposed by OSM can expose unexploited data and allows the stakeholders to understand the status of return and risk of their Cloud strategies easier than the use of other data analysis.