Multi-Criteria Evaluation of Partitioning Schemes for Real-Time Systems

TL;DR

This paper evaluates various partitioning algorithms for multiprocessor real-time scheduling, aiming to identify optimal heuristics and schedulability tests based on task set characteristics and constraints.

Contribution

It provides a comprehensive analysis of partitioning heuristics, their impact on schedulability tests, and compares Fixed Priority and EDF schedulers in this context.

Findings

Certain heuristics outperform others depending on task set and constraints.

The choice of task order significantly affects schedulability.

Performance differences between Fixed Priority and EDF vary with partitioning strategies.

Abstract

In this paper we study the partitioning approach for multiprocessor real-time scheduling. This approach seems to be the easiest since, once the partitioning of the task set has been done, the problem reduces to well understood uniprocessor issues. Meanwhile, there is no optimal and polynomial solution to partition tasks on processors. In this paper we analyze partitioning algorithms from several points of view such that for a given task set and specific constraints (processor number, task set type, etc.) we should be able to identify the best heuristic and the best schedulability test. We also analyze the influence of the heuristics on the performance of the uniprocessor tests and the impact of a specific task order on the schedulability. A study on performance difference between Fixed Priority schedulers and EDF in the case of partitioning scheduling is also considered.