NDLI: Scheduling Independent Tasks on Heterogeneous Distributed Computing Systems Using Multiobjective Optimization Approach on Multicore Processors

Content Provider	IEEE Xplore Digital Library
Author	Saranya, S. Revathi, S. Chitra, P. Venkatesh, P.
Copyright Year	2009
Abstract	The problem of mapping tasks and communications onto multiple machines and networks in a heterogeneous computing environment has been shown to be NP hard. Therefore, the development of heuristic techniques to find near optimal solutions is required. Many different types of mapping heuristics have been developed in recent years. This paper investigates the task-scheduling problem as a multiobjective problem and its solution based on the Genetic Algorithm (GA) heuristics.GA has been successfully used in solving many of such multiple objective optimization problems in literature. We have used the inherent parallel nature of GA in developing a parallel genetic algorithm on a multicore processor to solve this optimization problem. Simulation results show that the parallel GA helps in generating optimized schedules at a faster convergence rate.
Starting Page	481
Ending Page	483
File Size	257045
Page Count	3
File Format	PDF
ISBN	9781424453214
DOI	10.1109/ACT.2009.124
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-28
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	NP-hard Multicore processing Communication system control Optimal scheduling Task scheduling Control systems Telecommunication control Telecommunication computing Distributed computing Multicore processor Genetic algorithms Processor scheduling Genetic algorithm Multiobjective optimization Computer networks
Content Type	Text
Resource Type	Article

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