A Hybrid Strategy for Resource Allocation and Load Balancing in Virtualized Data Centers Using BSO Algorithms

In data centers are provided solution to the consumer and to the organization by means of store and process their data. When scheduling operation carrying more requirements for resources than it can hold, in this situation load balancing strategy distributes workloads across multiple servers to optimize the performances. However, resource allocation and load balancing is an inspiring problem for the cloud service providers to consumers in terms of Quality of Services. The proposed hybrid bacterial swarm optimization algorithm, achieve global seek over the entire search space through PSO while local search is achieved by BFO algorithm. This paper proposed a novel idea, how to tackle the scheduling problem by using hybrid load balancing techniques. The experimental results demonstrate that the projected algorithms overtake the existing SA, PSO, Dynamic ADS algorithms considerably by minimizing the operational cost, make-span and maximize the utilization of the resource.

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