Optimal Parallelization of Single Multi-Segment Real-Time Tasks for Global EDF

Abstract

Targeting global EDF scheduling, this article proposes an optimal algorithm for parallelizing tasks with parallelization freedom. For this, we extend the interference-based sufficient schedulability analysis and derive monotonic increasing properties of both tolerance and interference for the schedulability. Leveraging those properties, we propose a one-way search–based optimal algorithm with polynomial time complexity. We present a formal proof of the optimality of the proposed algorithm. We first address the single-segment task model and then extend to the multi-segment task model. Our extensive experiments through both simulation and actual implementation show that our proposed approach can significantly improve the schedulability.