ABSTRACT
Task scheduling is an NP-Hard problem, so it is one of the most pressing issues in the cloud computing environment. The primary goal of task scheduling is to schedule jobs on virtual machines and to improve processing performance throughout. In this work, we used the grey wolf optimizer algorithm with changes to the fitness function to accommodate multigoals in a single fitness the makespan and load are the objectives included inside the fitness to address task scheduling difficulties. The simulation results shown that the suggested approach grey wolf optimizer outperforms the other algorithms in terms of makespan and load variation.
