Affiliations: Department of Computer Science, Badji Mokhtar University, LabGED Laboratory, Annaba, Algeria
Correspondence:
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Corresponding author: Abir Achache, Department of Computer Science, Badji Mokhtar University, LabGED Laboratory, Po box 12, Annaba 23000, Algeria. E-mail: [email protected].
Abstract: Software as a Service is evolving as a leader model for cloud service delivery, enabling service providers to remotely deliver hosted, developed and managed software over the Internet. In parallel, some IT services are moving from traditional Internet services to cloud services based on peer-to-peer technologies. However, the P2P-based cloud is a large-scale, heterogeneous and highly dynamic environment whose performance is highly dependent on its ability to maintain persistent availability of SaaS services. In this paper, we propose an approach for improving SaaS service availability in order to meet service quality requirements and maintain performance in a P2P-Based cloud environment. It is mainly based on a new hybrid clustering mechanism that aims to provide a virtual and optimal infrastructure in order to organize the system peers into distinct clusters represented by virtual nodes forming together a virtual layer. This layer allows not only the distribution of peer providers but also the formation of condensed areas of each service of interest for a set of neighboring peers, which improve the availability probability of services in specific regions. In addition, a service availability measurement model was proposed based on the use of the system’s virtual layer taking into account different entities at different levels. The experimental results show that the proposed approach improves the probability of SaaS service availability and the reliability of the P2P-Cloud system. It responds mainly to the large-scale nature of distributed systems as well as making the best trade-off of maintaining QOS in terms of availability, performance and cost.
Keywords: Cloud computing, peer to peer, software as a service, availability, clustering, sequential hybridization clustering process, thresholded fuzzy c-means, hierarchical agglomerative clustering
