In this thesis, we study temperature-constrained multiprocessor real-time systems,
where real-time guarantees must be met without exceeding safe temperature levels
within the processors. We focus on Pfair scheduling algorithms, especially ERfair
scheduling scheme (a work-conserving extension to Pfair scheduling) as our main
multiprocessor real-time scheduling methodology. Then, we study the benefits of
simple reactive speed scaling as described in the real-time multiprocessor systems.
In this thesis, in support of the temperature-awareness, we extend the applicability
of the reactive speed scaling to global scheduling schemes for multiprocessors. We
propose temperature-aware scheduling and processor selection schemes motivated by
existing (thermally non-optimal) ERfair scheduling in order to reduce thermal stress
and therefore increase the processor utilization. Then, we show that the proposed
algorithm and reactive scheme can enhance the processor utilization compared with
any constant speed scheme on real-time multiprocessor systems. Additionally, we
show how the maximum schedulable utilization (MSU) for partitioning heuristics can
be determined on the temperature-constrained multiprocessor real-time systems.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/85913 |
| Date | 10 October 2008 |
| Creators | Koo, Ja-Ryeong |
| Contributors | Bettati, Riccardo |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | electronic, born digital |
Page generated in 0.0181 seconds