Cooperative game theoretic approach for job scheduling in cloud computing

Abstract

Cloud computing is the upcoming technology in current day scenario. It has emerged as a solution for providing computing resources as a service to the consumers in the form of infrastructure, platform and software. When multiple users request for services, cloud service provider has to schedule the requests to the available resources appropriately to satisfy each user's request to meet Service Level Agreements (SLAs) and also deadline constraints. Job scheduling in cloud environment is an important issue where the main aim is to schedule the jobs for effective resource utilization. Cloud service provider has to find the best possible scheduling in order to gain maximum profit from the service provided to the consumers. This paper aims at maximizing the resource utilization as well as profit for the service provider by cooperative game theory based approach for job scheduling in cloud environment. Additionally it also concentrates on minimizing the deadline violation and makespan for the jobs submitted by the user. Thus, new job scheduling technique is proposed using the concepts of game theory and genetic algorithm. This research work also focusses on cooperative game theoretic approach to provide Pareto optimal solution using Non-dominated Sorting Genetic Algorithm II (NSGA II).