Premium
Multiobjective differential evolution for scheduling workflow applications on global Grids
Author(s) -
Talukder A. K. M. Khaled Ahsan,
Kirley Michael,
Buyya Rajkumar
Publication year - 2009
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1417
Subject(s) - computer science , quality of service , differential evolution , heuristics , scheduling (production processes) , workflow , distributed computing , mathematical optimization , job shop scheduling , flexibility (engineering) , evolutionary algorithm , real time computing , routing (electronic design automation) , algorithm , computer network , mathematics , database , artificial intelligence , statistics , operating system
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.