Energy Efficient Task Provisioning for Distributed Cloud Networks using Meta Heuristic Multidisciplinary Technique

In Cloud computing most of the energy efficient techniques give more attention to energy consumption in task resources such as CPU and memory of the physical machines in cloud. The network bandwidth is used to connect users to the cloud were paid less attention, the cloud network transmission and switching components also consumes significant percentage of total energy consumption. In the proposed technique not only considering CPU and memory resources the network bandwidth is also included and developed an optimized energy efficient task provisioning for cloud data centres using both meta heuristic PSO (Particle Swarm Optimization) and Bat Algorithm, we combine major advantages of both the algorithm and develop an optimized energy efficient scheduling and migration algorithm that determines the proper number of tasks are assigned to each VM and migration is performed efficiently utilizing the bandwidth among the VMs to minimize the energy consumption. The implementation and verification of the proposed technique is evaluated using the Cloudsim.