An approach to dominant resource fairness in distributed environment

Qinyun Zhu, Jae C. Oh

Research output: Chapter in Book/Entry/PoemConference contribution

8 Scopus citations

Abstract

We study the multi-type resource allocation problem in distributed computing environment. Current approaches that guarantee the conditions of Dominant Resource Fairness (DRF) are centralized algorithms. However, as P2P cloud systems gain more popularity, distributed algorithms that satisfy conditions of DRF are in demand. So we propose a distributed algorithm that mostly satisfies DRF conditions. According to our simulation results, our distributed dominant resource fairness algorithm outperforms a naive distributed extension of DRF.

Original languageEnglish (US)
Title of host publicationCurrent Approaches in Applied Artificial Intelligence - 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015, Proceedings
EditorsChang-Hwan Lee, Yongdai Kim, Young Sig Kwon, Juntae Kim, Moonis Ali
PublisherSpringer Verlag
Pages141-150
Number of pages10
ISBN (Print)9783319190655
DOIs
StatePublished - 2015
Event28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015 - Seoul, Korea, Republic of
Duration: Jun 10 2015Jun 12 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9101
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015
Country/TerritoryKorea, Republic of
CitySeoul
Period6/10/156/12/15

Keywords

  • Distributed decision making
  • Distributed resource allocation
  • Dominant resource fairness

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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