Optimizing multi objective based workflow scheduling in cloud computing using black hole algorithm

Cloud computing employs parallel and distributed computing concepts to provide users with shared resources through the internet. One of the most important issues which are raised in a cloud environment is task scheduling on existing resources; so that on the one hand it can provide user's requirements, such as minimum run time or cost and on the other hand with the proper use of resources, can also cause service providers' benefits. In this paper we extended a recent heuristic algorithm called Black hole Optimization (BHO) and present a multi objective scheduling method for workflow application based on Pareto optimizer algorithm. Our proposed method can consider user requirements and also the interests of service providers. Using the balanced and unbalanced workflow we compared our proposed method with algorithms of SPEA2 and NSGA2 based on the parameters of completion time and cost and resource efficiency.