A response surface methodology approach to operating system scheduler tuning

George Anderson, Tshilidzi Marwala, Fulufhelo Vincent Nelwamondo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Tuning operating system components is a cyclical process involving setting parameters, evaluating the effect of the settings, making adjustments, and testing again. This is an expensive process, both taking a long time and requiring money to hire people to do it. In this paper we present a statistical approach to tuning of an operating system scheduler using Design of Experiments (DOE) and Response Surface Methodology (RSM). We make use of a benchmark and generate a response surface based on the runtime of the benchmark and three Linux scheduler parameters. We produce a model of the scheduler and optimize the parameter settings, minimizing the number of times the benchmark had to be run to find the optimal settings. In our experiment, we achieved an 11% performance improvement when the Linux scheduler ruus the benchmark. We also compared the scalability of the optimized and unoptimized schedulers and discovered that the optimized scheduler does much better in this regard. This was done without prior knowledge of optimal settings for the workload we used.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
Pages2684-2689
Number of pages6
DOIs
Publication statusPublished - 2010
Event2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010 - Istanbul, Turkey
Duration: 10 Oct 201013 Oct 2010

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)1062-922X

Conference

Conference2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
Country/TerritoryTurkey
CityIstanbul
Period10/10/1013/10/10

Keywords

  • Operating systems
  • Response surface methodology
  • Scheduling
  • System modeling & control

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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