Fast Rescheduling of Multiple Workflows to Constrained Heterogeneous Resources Using Multi-Criteria Memetic Computing

Algorithms

Wilfried Jakob¹  Sylvia Strack¹  Alexander Quinte¹  Günther Bengel²  Karl-Uwe Stucky¹ 

[1] Karlsruhe Institute of Technology (KIT), Institute of Applied Computer Science (IAI), P.O. Box 3640, Karlsruhe 76021, Germany; E-Mails:;Department of Computer Science, University of Applied Sciences Mannheim, Paul-Wittsack-Str. 10, Mannheim 68163, Germany; E-Mail:

关键词: scheduling;    Memetic Algorithms;    multi-criteria optimization;    constrained resources;    workflow scheduling;    fast scheduling;    empirical study;   

DOI  :  10.3390/a6020245

来源: mdpi

【 摘 要 】

This paper is motivated by, but not limited to, the task of scheduling jobs organized in workflows to a computational grid. Due to the dynamic nature of grid computing, more or less permanent replanning is required so that only very limited time is available to come up with a revised plan. To meet the requirements of both users and resource owners, a multi-objective optimization comprising execution time and costs is needed. This paper summarizes our work over the last six years in this field, and reports new results obtained by the combination of heuristics and evolutionary search in an adaptive Memetic Algorithm. We will show how different heuristics contribute to solving varying replanning scenarios and investigate the question of the maximum manageable work load for a grid of growing size starting with a load of 200 jobs and 20 resources up to 7000 jobs and 700 resources. Furthermore, the effect of four different local searchers incorporated into the evolutionary search is studied. We will also report briefly on approaches that failed within the short time frame given for planning.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.