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Generic Scheduling Method for Distributed Parallel Systems  

Kim, Hwa-Sung (광운대학교 전자공학부 네트워크 컴퓨팅 연구실)
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The Journal of Korean Institute of Communications and Information Sciences / v.28, no.1B, 2003 , pp. 27-32 More about this Journal
Abstract
This paper presents the Genetic Algorithm based Task Scheduling (GATS) method for the scheduling of programs with diverse embedded parallelism types in Distributed Parallel Systems, which consist of a set of loosely coupled parallel and vector machines connected via high speed networks The distributed parallel processing tries to solve computationally intensive problems that have several types of parallelism, on a suite of high performance and parallel machines in a manner that best utilizes the capabilities of each machine. When scheduling in distributed parallel systems, the matching of the parallelism characteristics between tasks and parallel machines rather than load balancing should be carefully handled with the minimization of communication cost in order to obtain more speedup. This paper proposes the based initialization methods for an initial population and the knowledge-based mutation methods to accommodate the parallelism type matching in genetic algorithms.
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