Multi-objective workflow scheduling in Amazon EC2
Juan J. Durillo • Radu Prodan
In this paper, we analyse MOHEFT, a Pareto-based list scheduling heuristic that provides the user with a set of tradeoff optimal solutions from which the one that bet-ter suits the user requirements can be manually selected. We demonstrate the potential of our method for multi-objective workflow scheduling on the commercial Ama-zon EC2 Cloud. We compare the quality of the MOHEFT tradeoff solutions with two state-of-the-art approaches us-ing different synthetic and real-world workflows: the classi-cal HEFT algorithm for single-objective scheduling and the SPEA2* genetic algorithm used in multi-objective optimi-sation problems.