Entropy-based scheduling performance in real-time multiprocessor systems

Abstract

In this paper, we present the performance analysis of the entropy-based scheduling approach in real-time multiprocessor systems. We analyze the effect of using the entropy-based scheduling layer in deadline-based (global Earliest Deadline First (EDF)), laxity-based (Least Laxity First (LLF)), and PFair-based (PD2) scheduling algorithms by measuring the number of preemptions, the number of job migrations, and the number of task migrations. The performance comparison results between the selected scheduling algorithms with their entropy-enabled versions showed that the entropy layer reduces the number of task migrations for all studied algorithms and reduces the number of job migrations for LLF and PD2.