Efficient Multi-resource, Multi-unit VCG Auction

Liran Funaro, Orna Agmon Ben-Yehuda, Assaf Schuster

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

Abstract

We consider the optimization problem of a multi-resource, multi-unit VCG auction that produces an exact, i.e., non-approximated, social welfare. We present an algorithm that solves this optimization problem with pseudo-polynomial complexity and demonstrate its efficiency via our implementation. Our implementation is efficient enough to be deployed in real systems to allocate computing resources in fine time-granularity. Our algorithm has a pseudo-near-linear time complexity on average (over all possible realistic inputs) with respect to the number of clients and the number of possible unit allocations. In the worst case, it is quadratic with respect to the number of possible allocations. Our experiments validate our analysis and show near-linear complexity. This is in contrast to the unbounded, nonpolynomial complexity of known solutions, which do not scale well for a large number of agents. For a single resource and concave valuations, our algorithm reproduces the results of a well-known algorithm. It does so, however, without subjecting the valuations to any restrictions and supports a multiple resource auction, which improves the social welfare over a combination of single-resource auctions by a factor of 2.5-50. This makes our algorithm applicable to real clients in a real system.

Original languageEnglish
Title of host publicationEconomics of Grids, Clouds, Systems, and Services - 16th International Conference, GECON 2019, Proceedings
EditorsKarim Djemame, Jörn Altmann, José Ángel Bañares, Orna Agmon Ben-Yehuda, Maurizio Naldi
PublisherSpringer
Pages231-246
Number of pages16
ISBN (Print)9783030360269
DOIs
StatePublished - 2019
Event16th International Conference on the Economics of Grids, Clouds, Systems, and Services, GECON 2019 - Leeds, United Kingdom
Duration: 17 Sep 201919 Sep 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11819 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on the Economics of Grids, Clouds, Systems, and Services, GECON 2019
Country/TerritoryUnited Kingdom
CityLeeds
Period17/09/1919/09/19

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2019.

Keywords

  • Cloud
  • d-MCK
  • MCK
  • MCMK
  • Resource allocation
  • VCG

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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