Metaheuristic based workflow scheduling in cloud environment

Workflow scheduling deals with the mapping of interdependent and compute intensives tasks to the system resources considering all application's requirements. Due to its elastic capabilities, the cloud has been instrumental in effective scheduling of workflow activities. This paper presents a genetic algorithm based metaheuristics to schedule workflow applications on cloud resources with an objective to improve both the makespan and resource utilization. The performance of proposed algorithm is tested for different workflow applications (Montage, Fork-Join, Epigenome) under various load conditions in a scalable environment.