doi: 10.4304/jsw.6.11.2308-2320
Two-level Hierarchical Scheduling Algorithm for Real-time Multiprocessor Systems
- LEAT research laboratory, University of Nice-Sophia Antipolis, Nice, France
Abstract
The Earliest Deadline First (EDF) scheduling algorithm has the least runtime complexity among joblevel fixed-priority algorithms for scheduling tasks on multiprocessor architectures. However, EDF suffers from suboptimality in multiprocessor systems. This paper proposes a new restricted migration-based scheduling algorithm for multiprocessor real-time systems, called <em>Two-level Hierarchical Scheduling Algorithm</em> (<em>2L-HiSA</em>), to address this sub-optimality. 2L-HiSA algorithm divides the problem of multiprocessor scheduling into a two-level hierarchy of schedulers. This algorithm works in two phases: i- A taskpartitioning phase in which, each task from application task set is assigned to a specific processor by following simple bin-packing approach. If a task can not be partitioned on any processor in the platform, it qualifies as migrating task. ii- A processor-grouping phase in which, processors are clustered together such that, per cluster, the unused fragmented computation power equivalent to at most one processor is available. We provide schedulability analysis and experimental evaluation to support our proposition. Moreover, our simulation results show an average difference of 18-folds in the number of preemptions and 10-folds in the number of task migrations under 2L-HiSA and PD2 algorithm.
Keywords
- Real-time Systems
- Multiprocessor
- Sched
How to Cite
Muhammad Khurram Bhatti, Cécile Belleudy, and Michel Auguin, "Two-level Hierarchical Scheduling Algorithm for Real-time Multiprocessor Systems," Journal of Software, vol. 6, no. 11, pp. 2308-2320, 2011. https://doi.org/ 10.4304/jsw.6.11.2308-2320
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
