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

چکیده مقاله

Cloud computing is one of the fields that has attracted a lot of attention in recent years. Task scheduling meaning the proper permutation of user requests on virtual machines is one of the most important challenges in the cloud environment due to the increase in virtual machines as well as the diversity of users with different service quality requirements and therefore task scheduling is a NP-hard problem. This becomes more complicated when quality of service objectives conflict with each other; therefore, service providers for the proper use of cloud environment capabilities require an optimal trade-off between the various objectives and in such cases heuristic algorithms can be used for optimal scheduling. To this end, we extended a recent heuristic algorithm called Black hole and considered dependency graph of workflow tasks. The proposed method combines the heuristic algorithm and decision-making method (AHP) to solve the multi-objective workflow scheduling problem on virtual machines. We converted the single-objective Black-hole algorithm into a multi-objective by using the AHP relationship, and then it is used to solve the scheduling problem. We have implemented our proposed method using the Workflowsim tool and have compared the results with multi-objective algorithms SPEA2 and NSGA2 based on the parameters of Makespan and cost and resource utilization using a balanced and unbalanced workflow. Copyright held by the author(s).