Accurate Optimal Scheduling In Cloud Computing Based On Hybrid Bacterial Evolutionary And Bees Mating Optimization Algorithm

For cloud computing, modern domestic and international information technology is a significant and frontier territory. The preparation of workflows plays a major role in cloud computing. The overall efficiency of the cloud system can be improved by planning workflows that are directly proportional to the accuracy of the planning methods.Optimization methods are most widely used to execute the task scheduling process. The optimization techniques used before performing the assignment scheduling method are particle swam optimization, genetic algorithm, and help vector machines. A new approach to conducting task planning processes based on the Hybrid Bacterial Evolution (HBE) framework is proposed in this paper.Various cost metrics such as execution cost, completion cost is considered to perform the fitness evaluation process. To evaluate the performance, various performance metrics such as Schedule Length Ratio (SLR), makes pan and speedup are evaluated. From the simulation result, it is very clear that the proposed techniques produced best performance in terms of all quality evaluation metrics.