Efficient Workflow Scheduling algorithm in cloud computing using Whale Optimization

Task Scheduling is a tremendous challenge in cloud computing as tasks are varied in terms of their processing capacity and interdependent on each other i.e. workflows. Therefore, it is difficult to map workflows to suitable virtual resources in cloud environment. Many authors developed various schedulers, which addresses makespan and Quality of service metrics. Authors have not addressed parameters makespan in combination with migration time, which also affects performance of cloud computing environment. In this manuscript, a new workflow-scheduling mechanism is proposed, which takes priorities of tasks and schedules tasks effectively on to corresponding virtual resources. Whale optimization algorithm as the methodology to model this algorithm. Extensive simulations carried out on workflowsim simulator. It was evaluated aganist existing PSO, CS, ACO, GA algorithms. Finally, from simulation results, it was identified that makespan, migration time and energy consumption were minimized to a good extent.