A Hybrid Bio-Inspired Algorithm for Scheduling and Resource Management in Cloud Environment - 2017


During this paper, we have a tendency to propose a completely unique HYBRID Bio-Inspired algorithm for task scheduling and resource management, since it plays an necessary role in the Cloud Computing surroundings. Conventional scheduling algorithms like Spherical Robin, First Come back First Serve, Ant Colony Optimization etc. have been widely used in many Cloud Computing systems. Cloud receives clients tasks during a rapid rate and allocation of resources to these tasks should be handled in an intelligent manner. During this proposed work, we have a tendency to allocate the tasks to the virtual machines in an economical manner using Modified Particle Swarm Optimization algorithm and then allocation / management of resources (CPU and Memory), as demanded by the tasks, is handled by proposed HYBRID Bio-Inspired algorithm (Changed PSO + Changed CSO). Experimental results demonstrate that our proposed HYBRID algorithm outperforms peer research and benchmark algorithms (ACO, MPSO, CSO, RR and Actual algorithm based on branch-and-sure technique) in terms of efficient utilization of the cloud resources, improved reliability and reduced average response time..

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