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Efficient Multi-resource, Multi-unit VCG Auction

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Economics of Grids, Clouds, Systems, and Services (GECON 2019)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 11819))

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.

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Notes

  1. 1.

    The auction is named after William Vickrey, Edward H. Clarke, and Theodore Groves.

  2. 2.

    Available from: https://bitbucket.org/funaro/vecfunc-vcg.

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Acknowledgments

We thank Deborah Miller, Sharon Kessler, Hadas Shachnai, Tamar Camus, Ido Nachum, Danielle Movsowitz and Shunit Agmon for fruitful discussions. This work was partially funded by the Hasso Platner Institute, and by the Pazy Joint Research Foundation.

Author information

Authors and Affiliations

  1. Computer Science Department, Technion—Israel Institute of Technology, Haifa, Israel

    Liran Funaro, Orna Agmon Ben-Yehuda & Assaf Schuster

  2. Caesarea Rothschild Institute for Interdisciplinary Applications of Computer Science, University of Haifa, Haifa, Israel

    Orna Agmon Ben-Yehuda

Authors
  1. Liran Funaro
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  2. Orna Agmon Ben-Yehuda
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  3. Assaf Schuster
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Corresponding authors

Correspondence to Liran Funaro , Orna Agmon Ben-Yehuda or Assaf Schuster .

Editor information

Editors and Affiliations

  1. University of Leeds, Leeds, UK

    Karim Djemame

  2. Seoul National University, Seoul, Korea (Republic of)

    Jörn Altmann

  3. University of Zaragoza, Zaragoza, Spain

    José Ángel Bañares

  4. Technion – Israel Institute of Technology and University of Haifa, Haifa, Israel

    Orna Agmon Ben-Yehuda

  5. LUMSA University, Rome, Italy

    Maurizio Naldi

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Funaro, L., Agmon Ben-Yehuda, O., Schuster, A. (2019). Efficient Multi-resource, Multi-unit VCG Auction. In: Djemame, K., Altmann, J., Bañares, J., Agmon Ben-Yehuda, O., Naldi, M. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2019. Lecture Notes in Computer Science(), vol 11819. Springer, Cham. https://doi.org/10.1007/978-3-030-36027-6_20

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  • DOI: https://doi.org/10.1007/978-3-030-36027-6_20

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