Task scheduling in heterogeneous cloud environment using mean grey wolf optimization algorithm

The primary objective of task scheduling involves scheduling the task on resources and minimizing the objective of the schedule. In this study, we proposed mean grey wolf optimization algorithm to enhance the system performance there by depleting the scheduling issues. The main objective of this method is minimizing the makespan and energy consumption. The objective of the proposed algorithms has been evaluated using CloudSim toolkit for standard workload. The outcome of the simulation result shows that the proposed Mean GWO algorithm renders comparatively ample result than the other existing algorithms. (C) 2018 The Korean Institute of Communications and Information Sciences (KICS). Publishing Services by Elsevier B.V.