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AN IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR LOAD BALANCED FAULT TOLERANT VIRTUAL MACHINE SCHEDULING IN COMPUTATIONAL CLOUD

V.M. Sivagami, K.S. Easwarakumar

Abstract


Cloud computing is the delivery of computing services over the Internet. The main objective of this work is to to provide combined resource provisioning and scheduling strategy for executing scientific workflows on IaaS Clouds. The scenario was modeled as an optimization problem which aims to minimize the overall execution cost while meeting a user defined deadline and was solved using the meta-heuristic optimization algorithm, PSO. The proposed approach incorporates basic IaaS Cloud principles such as a pay-as-you-go model, heterogeneity, elasticity, and dynamicity of the resources. Furthermore, this work includes other characteristics typical of IaaS platforms such as performance variation and VM boot time.

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DOI: http://dx.doi.org/10.6084/ijact.v0i0.536

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