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Semi-Federated Scheduling of Parallel Real-Time Tasks on Multiprocessors
Hong Kong Polytech Univ, Hong Kong, Hong Kong, Peoples R China.;Beihang Univ, Sch Comp Sci & Engn, State Key Lab Virtual Real Technol & Syst, Beijing, Peoples R China..
Hong Kong Polytech Univ, Hong Kong, Hong Kong, Peoples R China..
Beihang Univ, Sch Comp Sci & Engn, State Key Lab Virtual Real Technol & Syst, Beijing, Peoples R China..
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Northeastern Univ, Shenyang, Liaoning, Peoples R China..
2017 (English)In: 2017 IEEE Real-Time Systems Symposium (RTSS), IEEE, 2017, p. 80-91Conference paper, Published paper (Refereed)
Abstract [en]

Federated scheduling is a promising approach to schedule parallel real-time tasks on multi-cores, where each heavy task exclusively executes on a number of dedicated processors, while light tasks are treated as sequential sporadic tasks and share the remaining processors. However, federated scheduling suffers resource waste since a heavy task with processing capacity requirement x + is an element of (where x is an integer and 0 < is an element of < 1) needs x+ 1 dedicated processors. In the extreme case, almost half of the processing capacity is wasted. In this paper we propose the semi-federate scheduling approach, which only grants x dedicated processors to a heavy task with processing capacity requirement x+ is an element of, and schedules the remaining is an element of part together with light tasks on shared processors. Experiments with randomly generated task sets show the semi-federated scheduling approach significantly outperforms not only federated scheduling, but also all existing approaches for scheduling parallel real-time tasks on multi-cores.

Place, publisher, year, edition, pages
IEEE, 2017. p. 80-91
Series
Real-Time Systems Symposium-Proceedings, ISSN 1052-8725
Keywords [en]
real-time-scheduling, parallel-tasks, DAG, federated-scheduling
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:uu:diva-351171DOI: 10.1109/RTSS.2017.00015ISI: 000426466700008ISBN: 978-1-5386-1414-3 (electronic)OAI: oai:DiVA.org:uu-351171DiVA, id: diva2:1209840
Conference
38th IEEE Real-Time Systems Symposium (RTSS), DEC 05-08, 2017, Paris, FRANCE
Available from: 2018-05-24 Created: 2018-05-24 Last updated: 2018-05-24Bibliographically approved

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Yi, Wang

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