Cauchy Particle Swarm Optimization (CPSO) Based Migrations of Tasks in a Virtual Machine

Cloud computing technology helps to resolve the problem in storage management by providing virtual resources end users. But, overloading of machines results degradation performances as well it increases energy consumption machines. Several techniques were used determine workloads cloud and then apply migration algorithm for efficient utilization resources. process depends on past outputs only few step ahead predictions. Most allocate based all attributes. This higher processing time allocation. Hence, this, an attribute resource allocation is proposed utilize effectively user demands. The concept virtualization reduce cost individual hardware setups run processes. In computing, processes improve services. modified Principal component analysis relief selection. Then, selected processed with hybrid Cauchy particle swarm method tested google cluster dataset its performance evaluated terms count power consumption. compared automated technique (ALM) forecast (CF-LA). outperforms both existing reducing between MPCA CPSO best allocating dynamically cloud.