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Authors: Diana Gudu 1 ; Gabriel Zachmann 2 ; Marcus Hardt 1 and Achim Streit 1

Affiliations: 1 Karlsruhe Institute of Technology, Germany ; 2 Karlsruhe Institute of Technology and Baden-Wuerttemberg Cooperative State University, Germany

ISBN: 978-989-758-275-2

Keyword(s): Combinatorial Auction, Resource Allocation, Cloud Computing, Approximate Algorithm.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Distributed and Mobile Software Systems ; Economic Agent Models ; Enterprise Information Systems ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Multi-Agent Systems ; Software Engineering ; Symbolic Systems

Abstract: There is an increasing trend towards market-driven resource allocation in cloud computing, which can address customer requirements for flexibility, fine-grained allocation, as well as improve provider revenues. We formulate the cloud resource allocation as a double combinatorial auction. However, combinatorial auctions are NP-hard problems. Determining the allocation optimally is thus intractable in most cases. Various heuristics have been proposed, but their performance and quality of the obtained solutions are highly dependent on the input. In this paper, we perform an extensive empirical comparison of several approximate allocation algorithms for double combinatorial auctions. We discuss their performance, economic efficiency, and the reasons behind the observed variations in approximation quality. Finally, we show that there is no clear winner: no algorithm outperforms the others in all test scenarios. Furthermore, we introduce a novel artificial input generator for combinatorial auctions which uses parameterized random distributions for bundle sizes, resource type selection inside a bundle, and the bid values and reserve prices. We showcase its flexibility, required for thorough benchmark design, through a wide range of test cases. (More)

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Paper citation in several formats:
Gudu, D.; Zachmann, G.; Hardt, M. and Streit, A. (2018). Approximate Algorithms for Double Combinatorial Auctions for Resource Allocation in Clouds: An Empirical Comparison.In Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-275-2, pages 58-69. DOI: 10.5220/0006593900580069

@conference{icaart18,
author={Diana Gudu. and Gabriel Zachmann. and Marcus Hardt. and Achim Streit.},
title={Approximate Algorithms for Double Combinatorial Auctions for Resource Allocation in Clouds: An Empirical Comparison},
booktitle={Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2018},
pages={58-69},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006593900580069},
isbn={978-989-758-275-2},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Approximate Algorithms for Double Combinatorial Auctions for Resource Allocation in Clouds: An Empirical Comparison
SN - 978-989-758-275-2
AU - Gudu, D.
AU - Zachmann, G.
AU - Hardt, M.
AU - Streit, A.
PY - 2018
SP - 58
EP - 69
DO - 10.5220/0006593900580069

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