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This project has been proposed for monitoring working process of internal and external clouds. Here, Public clouds provide Infrastructure as a Service (IaaS) to users who do not own sufficient compute resources. It faces the problem of the scheduling tasks to meet the peak demand while preserving Quality-of-Service (QoS). By using Standard PSO easily traps into local optima and also is not robust for difficult problem instances. In the Proposed work, resource allocation framework in which an IaaS provider can outsource its tasks to External Clouds (ECs) when its own resources are not sufficient to meet the demand. Each task has a strict deadline to meet, so that the resource allocation problem can be considered as a deadline constrained task scheduling (DCTS) one. An integer programming formulation of the DCTS problem is established, with the objective ofmaximizing the profit of the private cloud on the premise of guaranteeing QoS. while increases exponentially with the growth of the number of tasks, using the particle swarm optimization (PSO) based scheduling approach is proposed to solve this problem. PSO has the advantages of easily realizing and quickly converging, so that this scheduling approach is able to get an optimal or suboptimal solution in a shorter computational time than the large size problems. It will increase the profit and also increase the problems of nontrivial size.

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How to Cite
C.Vasuki, V.Jamuna, V.Kiruthiga, M.Princy Priscilla, A.Tamil arasan, & B.Kirubaharan. (2017). A securable data storage framework in cloud computing . International Journal of Intellectual Advancements and Research in Engineering Computations, 5(2), 1287–1290. Retrieved from