Multiobjective differential evolution for scheduling workflow applications on global Grids

Authors:
A. K. M. Khaled Ahsan Talukder;Michael Kirley;Rajkumar Buyya
Affiliations:
Department of Computer Science and Software Engineering, The University of Melbourne, Parkville, Victroia 3010, Australia;Department of Computer Science and Software Engineering, The University of Melbourne, Parkville, Victroia 3010, Australia;Department of Computer Science and Software Engineering, The University of Melbourne, Parkville, Victroia 3010, Australia
Venue:
Concurrency and Computation: Practice & Experience - Special Issue: Advanced Strategies in Grid Environments
Year:
2009

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Abstract

Most algorithms developed for scheduling applications on global Grids focus on a single Quality of Service (QoS) parameter such as execution time, cost or total data transmission time. However, if we consider more than one QoS parameter (e.g. execution cost and time, which may be in conflict) then the problem becomes more challenging. To handle such scenarios, it is convenient to use heuristics rather than a deterministic algorithm. In this paper, we have proposed a workflow execution planning approach using Multiobjective Differential Evolution (MODE). Our goal was to generate a set of trade-off schedules according to two user specified QoS requirements (time and cost), which will offer more flexibility to users when estimating their QoS requirements. We have compared our results with a well-known baseline algorithm ‘Pareto-archived Evolutionary Strategy (PAES)’. Simulation results show that the modified MODE is able to find significantly better spread of compromise solutions compared with that of PAES. Copyright © 2009 John Wiley & Sons, Ltd.