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DOI: 10.4230/LIPIcs.FSTTCS.2016.7
URN: urn:nbn:de:0030-drops-68429
URL: https://drops.dagstuhl.de/opus/volltexte/2016/6842/
Baruah, Sanjoy ; Easwaran, Arvind ; Guo, Zhishan
Mixed-Criticality Scheduling to Minimize Makespan
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Abstract
In the mixed-criticality job model, each job is characterized by two execution time parameters, representing a smaller (less conservative) estimate and a larger (more conservative) estimate on its actual, unknown, execution time. Each job is further classified as being either less critical or more critical. The desired execution semantics are that all jobs should execute correctly provided all jobs complete upon being allowed to execute for up to the smaller of their execution time estimates, whereas if some jobs need to execute beyond their smaller execution time estimates (but not beyond their larger execution time estimates), then only the jobs classified as being more critical are required to execute correctly. The scheduling of collections of such mixed-criticality jobs upon identical multiprocessor platforms in order to minimize the makespan is considered here.
BibTeX - Entry
@InProceedings{baruah_et_al:LIPIcs:2016:6842,
author = {Sanjoy Baruah and Arvind Easwaran and Zhishan Guo},
title = {{Mixed-Criticality Scheduling to Minimize Makespan}},
booktitle = {36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2016)},
pages = {7:1--7:13},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-027-9},
ISSN = {1868-8969},
year = {2016},
volume = {65},
editor = {Akash Lal and S. Akshay and Saket Saurabh and Sandeep Sen},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2016/6842},
URN = {urn:nbn:de:0030-drops-68429},
doi = {10.4230/LIPIcs.FSTTCS.2016.7},
annote = {Keywords: Scheduling, Mixed criticality, Identical parallel machines, Makespan minimization, Approximation algorithm.}
}
| Keywords: | Scheduling, Mixed criticality, Identical parallel machines, Makespan minimization, Approximation algorithm. | |
| Seminar: | 36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2016) | |
| Issue date: | 2016 | |
| Date of publication: | 10.12.2016 |
