Partitioned scheduling of parallel real-time tasks on multiprocessor systems

Abstract

In this paper, we focus on the scheduling of periodic fork-join real-time tasks on multiprocessor systems. Parallel real-time tasks in the fork-join model have strict parallel segments without laxity. We propose a partitioned scheduling algorithm which increases the laxity of the parallel segments and therefore the schedulability of tasksets of this model. A similar algorithm has been proposed in the literature but it produces job migrations. Our algorithm eliminates the use of job migrations in order to create a portable algorithm that can be implemented on a standard Linux kernel. Results of extensive simulations are provided in order to analyze the schedulability of the proposed algorithm, and to provide comparisons with the other algorithm proposed in the literature.

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