Game multi objective scheduling algorithm for scientific workflows in cloud computing

Cloud computing is the latest utility computing that enables the dynamic provisioning for applications over the Internet. Cloud computing provide large number of opportunities to solve large scale scientific problems. Scheduling the tasks in the workflows is an NP-hard problem and in this work we focus on optimizing the scheduling process of the workflow. Scheduling of the workflow applications that satisfy the given constraints for the scientific tasks is an essential requirement for the workflow scheduling. Mapping of each task to suitable resource and allowing the task to satisfy performance constraints is the main aim of this paper. In the present work we propose game theoretic algorithm for multi-objective scheduling of scientific workflows in cloud computing environment. The scheduling problem is formulated as a new sequential cooperative game based on two user objectives that are execution time and economic cost while fulfilling two constraints network bandwidth and storage requirements. We call it as Game Multi Objective (GMO) algorithm. In this paper we apply Game Multi Objective algorithm for minimizing the execution time and cost of an workflow application.