Competitive analysis of task scheduling algorithms on a fault-prone machine and the impact of resource augmentation

Antonio Fernández Anta, Chryssis Georgiou, Dariusz R. Kowalski, Elli Zavou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Reliable task execution on machines that are prone to unpredictable crashes and restarts is both important and challenging, but not much work exists on the analysis of such systems. We consider the online version of the problem, with tasks arriving over time at a single machine under worst-case assumptions. We analyze the fault-tolerant properties of four popular scheduling algorithms: Longest In System (LIS), Shortest In System (SIS), Largest Processing Time (LPT) and Shortest Processing Time (SPT). We use three metrics for the evaluation and comparison of their competitive performance, namely, completed load, pending load, and latency. We also investigate the effect of resource augmentation in their performance, by increasing the speed of the machine. Hence, we compare the behavior of the algorithms for different speed intervals and show that there is no clear winner with respect to all the three considered metrics. While SPT is the only algorithm that achieves competitiveness on completed load for small speed, LIS is the only one that achieves competitiveness on latency (for large enough speed).

Original languageEnglish (US)
Title of host publicationAdaptive Resource Management and Scheduling for Cloud Computing - 2nd International Workshop, ARMS-CC 2015 Held in Conjunction with ACM Symposium on Principles of Distributed Computing, PODC 2015 Donostia-San Sebastián, Spain, July 20, 2015, Revised Selected Papers
EditorsFlorin Pop, Maria Potop-Butucaru
PublisherSpringer Verlag
Pages1-16
Number of pages16
ISBN (Print)9783319284477
DOIs
StatePublished - Jan 1 2015
Externally publishedYes
Event2nd International Workshop on Adaptive Resource Management and Scheduling for Cloud Computing, ARMS-CC 2015 - Donostia-San Sebastián, Spain
Duration: Jul 20 2015Jul 20 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9438
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Workshop on Adaptive Resource Management and Scheduling for Cloud Computing, ARMS-CC 2015
CountrySpain
CityDonostia-San Sebastián
Period7/20/157/20/15

Keywords

  • Competitive analysis
  • Failures
  • Online algorithms
  • Resource augmentation
  • Scheduling
  • Task sizes

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Fernández Anta, A., Georgiou, C., Kowalski, D. R., & Zavou, E. (2015). Competitive analysis of task scheduling algorithms on a fault-prone machine and the impact of resource augmentation. In F. Pop, & M. Potop-Butucaru (Eds.), Adaptive Resource Management and Scheduling for Cloud Computing - 2nd International Workshop, ARMS-CC 2015 Held in Conjunction with ACM Symposium on Principles of Distributed Computing, PODC 2015 Donostia-San Sebastián, Spain, July 20, 2015, Revised Selected Papers (pp. 1-16). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9438). Springer Verlag. https://doi.org/10.1007/978-3-319-28448-4_1