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Multi-resource Fair Allocation with Bounded Number of Tasks in Cloud Computing Systems

  • Weidong Li
  • Xi Liu
  • Xiaolu Zhang
  • Xuejie Zhang
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 768)

Abstract

Dominant resource fairness (DRF) is a popular mechanism for multi-resource allocation in cloud computing systems. In this paper, we consider the problem of multi-resource fair allocation with bounded number of tasks. We propose the lexicographically max-min normalized share (LMMNS) fair allocation mechanism, which is a natural generalization of DRF, and design a non-trivial optimal algorithm to find a LMMNS fair allocation, whose running time is linear in the number of users. Then, we prove that LMMNS satisfies envy-freeness and group strategy-proofness, and analyze the approximation ratios of LMMNS with some assumptions, by exploiting the properties of the optimal solution.

Keywords

Lexicographically max-min normalized share Dominant resource fairness Multi-resource fair allocation Approximation ratio 

Notes

Acknowledgment

The work is supported in part by the National Natural Science Foundation of China [Nos. 61662088, 11301466], the Natural Science Foundation of Yunnan Province of China [No. 2014FB114] and IRTSTYN.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • Weidong Li
    • 1
    • 2
  • Xi Liu
    • 1
  • Xiaolu Zhang
    • 1
  • Xuejie Zhang
    • 1
  1. 1.Yunnan UniversityKunmingPeople’s Republic of China
  2. 2.Dianchi College of Yunnan UniversityKunmingPeople’s Republic of China

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