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Mixed-Criticality Scheduling to Minimize Makespan

Authors Sanjoy Baruah, Arvind Easwaran, Zhishan Guo

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Sanjoy Baruah
Arvind Easwaran
Zhishan Guo

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Sanjoy Baruah, Arvind Easwaran, and Zhishan Guo. Mixed-Criticality Scheduling to Minimize Makespan. In 36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 65, pp. 7:1-7:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016) https://doi.org/10.4230/LIPIcs.FSTTCS.2016.7

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.

Subject Classification

Keywords
  • Scheduling
  • Mixed criticality
  • Identical parallel machines
  • Makespan minimization
  • Approximation algorithm.

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References

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