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A linear programming driven genetic algorithm for meta-scheduling on utility grids


Garg, SK and Konugurthi, P and Buyya, R, A linear programming driven genetic algorithm for meta-scheduling on utility grids, Proceedings of the 16th International Conference on Advanced Computing and Communication 2008, 14-17 December 2008, Chennai, India, pp. 19-26. ISBN 978-1-4244-2963-9 (2008) [Refereed Conference Paper]

Copyright Statement

Copyright 2009 IEEE

DOI: doi:10.1109/ADCOM.2008.4760422


The user-level brokers in grids consider individual application QoS requirements and minimize their cost without considering demands from other users. This results in contention for resources and sub-optimal schedules. Meta-scheduling in grids aims to address this scheduling problem, which is NP hard due to its combinatorial nature. Thus, many heuristic-based solutions using Genetic Algorithm (GA) have been proposed, apart from traditional algorithms such as Greedy and FCFS. We propose a Linear Programming/Integer Programming model (LP/IP) for scheduling these applications to multiple resources. We also propose a novel algorithm LPGA (Linear programming driven Genetic Algorithm) which combines the capabilities of LP and GA. The aim of this algorithm is to obtain the best meta-schedule for utility grids which minimize combined cost of all users in a coordinated manner. Simulation results show that our proposed integrated algorithm offers the best schedule having the minimum processing cost with negligible time overhead.

Item Details

Item Type:Refereed Conference Paper
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Distributed systems and algorithms
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Garg, SK (Dr Saurabh Garg)
ID Code:93892
Year Published:2008
Deposited By:Information and Communication Technology
Deposited On:2014-08-20
Last Modified:2015-03-24

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