Biogeography-based optimization for optimal job scheduling in cloud computing

We propose a novel BBO algorithm with the tradeoff between exploration and exploitation.The job scheduling problems are formulated theoretically.We optimize the job scheduling using our BBO algorithms.The statistical study (non-parametric) is introduced to analyze our experimental results. In cloud computing, the resources are dynamic and their performance or load can change frequently over time. Cloud resource management needs the functionality for NP-complete scheduling of jobs. The objective of this paper is to optimize the job scheduling using biogeography-based optimization (BBO). BBO migration is used to change existing solutions and to adapt new good solutions. BBO offers the advantage of adaptive process, which is developed for binary integer job scheduling problem in cloud computing. Experimental results show that the performance of the proposed methods are better than the considered other methods in job scheduling problems.