A Novel Based Resource Allocation Method on Cloud Computing Environment Using Hybrid Differential Evolution Algorithm

Nowadays people are connected to the internet and access various Cloud services and store information. Cloud computing assembles a massive number of virtualized services like infrastructure, platform and software. Cloud computing ensures access to shared resources and common infrastructure and giving services on demand over a network to fulfill dynamic business requests. Implementation of effective multi-objective Resource Allocation is a major issue in cloud computing. Several hybrid optimization algorithms exist to resolve the Resource allocation issues. Genetic Algorithm hybrid with PSO (GAPSO) and Differential Evolution Algorithm hybrid with PSO (DEPSO) are hybrid algorithms of GA and DE, they perform better than ordinary GA and DE. This paper demonstrates the advantage of GAPSO and DEPSO over traditional GA and DE techniques and it exploits multi-objective task scheduling using differential evolution with PSO in cloud data centers. Empirical results show that the proposed DEPSO technique improves the efficiency of multi-objective resource allocation. The experimental results prove that DEPSO is able to achieve a better performance than GAPSO.