Scheduling Gangs with Different Distributions in Gangs' Degree of Parallelism in a Multi-Site System

Gang scheduling is considered to be a highly effective task scheduling policy for distributed systems. Gangs are jobs which consist of a number of interacting tasks which are scheduled to run simultaneously on distinct processors. Simulation experiments are conducted to address performance issues which concern the impact of the variability in gangs’ degree of parallelism in the case of implemented migrations. A simulation model consisting of two sites is used to provide results on the performance of the system.

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