Multi-objective Strategy for Energy Efficient Workflow Scheduling in Cloud Computing

Scheduling the workflow task to the cloud resources is a recognized N-P hard problem. The users involved in a cloud have diverse interests in scheduling problem. In addition to the conventional objectives like makespan, budget, and deadline, optimized in workflow scheduling, taking into consideration the green aspect of cloud, enhance the problem complication. Furthermore, the interests of a clouds users are conflicting, and satisfying all these interests simultaneously is a large problem. In this paper, we proposed a new Genetic algorithm called MOGA for workflow scheduling which provides multiple objectives in a cloud-environment. By comparing with different algorithm the results show that our proposed algorithm has significantly improved not only in terms of budget, deadline, and energy but also improved the utilization of clouds resources as compared to the other algorithms of this work.