Cloudy GSA for load scheduling in cloud computing

Scheduling of load and data plays an important role in the efficient utilization of the resources from one cloudlet to another cloudlet in the cloud computing environment. Cloud computing is an incremental paradigm to brighten the world with its great vision of providing the power of distributed computing through virtual approach. Resource allocation plays an important role in the optimal handling of the load scheduling problem using static and meta-heuristic approaches. The Gravitational Search Algorithm (GSA) is a nature-inspired meta-heuristic optimization technique which is used for solving the load scheduling problem in the cloud computing environment and is based on Newtons gravitational law dealing with gravity. This paper proposes a near optimal load scheduling algorithm named Cloudy-GSA to minimize the transfer time and the total cost incurred in scheduling the cloudlets to the VMs. These are achieved by increased exploitation of VMs using the particles based on fitness values. The Cloudy-GSA algorithm is implemented on the CloudSim and has been compared with the existing popular algorithms. The results of the algorithm are converged and statistically analysed over a set of iterations. As evident from the results, the proposed Cloudy-GSA algorithm minimizes the transfer time and the total cost for scheduling the load than the existing algorithms. (C) 2018 Elsevier B.V. All rights reserved.