Truth revelation in approximately efficient combinatorial auctions

Lehmann, Daniel; O'Callaghan, Liadan; Shoham, Yoav

doi:10.1145/336992.337016

Cited by 175 publications

(212 citation statements)

References 11 publications

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“…However, the requirement of having dominant strategies limits the existence of feasible allocation algorithms in combinatorial auctions for unknown multi-minded buyers [23], [28]. We turn our attention to another well-known game-theoretic concept: implementation in undominated strategies.…”

Section: Economic Propertiesmentioning

confidence: 99%

AEGIS: An Unknown Combinatorial Auction Mechanism Framework for Heterogeneous Spectrum Redistribution in Noncooperative Wireless Networks

Zheng

Tang

et al. 2016

IEEE/ACM Trans. Networking

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With the growing deployment of wireless communication technologies, radio spectrum is becoming a scarce resource. Auctions are believed to be among the most effective tools to solve or relieve the problem of radio spectrum shortage. However, designing a practical spectrum auction mechanism has to consider five major challenges: strategic behaviors of unknown users, channel heterogeneity, preference diversity, channel spatial reusability, and social welfare maximization. Unfortunately, none of the existing work fully considered these five challenges. In this paper, we model the problem of heterogeneous spectrum allocation as a combinatorial auction, and propose AEGIS, which is the first framework of unknown combinatorial Auction mEchanisms for heteroGeneous spectrum redIStribution. AEGIS contains two mechanisms, namely AEGIS-SG and AEGIS-MP. AEGIS-SG is a direct revelation combinatorial spectrum auction mechanism for unknown single-minded users, achieving strategy-proofness and approximately efficient social welfare. We further design an iterative ascending combinatorial auction, namely AEGIS-MP, to adapt to the scenario with unknown multi-minded users. AEGIS-MP is implemented in a set of undominated strategies and has a good approximation ratio. We evaluate AEGIS on two practical datasets: Google Spectrum Database and GoogleWiFi. Evaluation results show that AEGIS achieves much better performance than the state-of-the-art mechanisms.Index Terms-Channel allocation, mechanism design, wireless network.

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Section: Economic Propertiesmentioning

confidence: 99%

AEGIS: An Unknown Combinatorial Auction Mechanism Framework for Heterogeneous Spectrum Redistribution in Noncooperative Wireless Networks

Zheng

Tang

et al. 2016

IEEE/ACM Trans. Networking

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“…In auction design, we first study the case that the bidders are single-minded [6], i.e., they can only accept allocations of either the whole requested bundle (or any superset) or nothing. Note that this is the assumption for most existing work on cloud auctions (e.g., [16], [23]) and false-name-proof auctions (e.g., [8], [19]).…”

Section: A System Modelmentioning

confidence: 99%

eBay in the Clouds: False-Name-Proof Auctions for Cloud Resource Allocation

Wang

Tang

et al. 2015

2015 IEEE 35th International Conference on Distributed Computing Systems

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The paradigm of cloud computing has spontaneously prompted a wide interest in auction-based mechanisms for cloud resource allocation. To eliminate market manipulation, a number of strategy-proof (a.k.a. truthful) cloud auction mechanisms have been recently proposed by enforcing bidders to bid their true valuations of the cloud resources. However, as discovered in this paper, they would suffer from a new cheating pattern, named false-name bids, where a bidder can gain profit by submitting bids under multiple fictitious names (e.g., multiple e-mail addresses). Such false-name cheating is easy to make but hard to detect in cloud auctions. To tackle this issue, we propose FAITH, a new False-name-proof Auction for vIrTual macHine instance allocation, that is proven both strategy-proof and false-nameproof by our theoretical analysis. When N users compete for M different types of computing instances with multiple units, FAITH achieves a lower time complexity of O(N log N +NM) compared to exiting cloud auction designs. We further extend FAITH to support range-based requests as desired in practice for flexible auction. Through extensive simulation experiments, we show that FAITH highly improves auction efficiency, outperforming the extended mechanisms of conventional false-name-proof auctions in terms of generated revenue and social welfare by up to 220% and 140%, respectively.

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“…Recently, spectrum auctions have received extensive research efforts in the literature [1]- [7]. In [1], Zhou et al utilized the greedy allocation together with the critical value based pricing in [15] to design a truthful and computationally efficient spectrum auction mechanism under the bidder interference constraints. In [5], the same authors proposed Athena, a collusion-resistant spectrum auction mechanism using APM [16].…”

Section: Eligible Bidder Satisfaction Ratiomentioning

confidence: 99%

Fair Pricing in the Sky: Truthful Frequency Allocation with Dynamic Spectrum Supply

Sun

Wang

Ren

et al. 2014

2014 IEEE 22nd International Conference on Network Protocols

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Spectrum auctions, which allow a spectrum owner to sell licenses for signal transmission over specific bands, can allocate scarce spectrum resources quickly to the users that value them most and have received a great deal of research attention in recent years. While enabling reusability-driven spectrum allocation, truthful spectrum auction designs are also expected to provide price fairness for homogeneous channels, online auction with unknown and dynamic spectrum supplies, and bounded system performance. Existing works, however, lack of such designs due to the inherent technically challenging nature. In this paper, we study the problem of allocating channels to spectrum users with homogeneous/heterogenous demands in a setting where idle channels are arriving dynamically, with the goal of maximizing social welfare. Taking spectrum reusability into consideration, we present a suite of novel and efficient spectrum auction algorithms that achieve fair pricing for homogeneous channels, strategyproofness, online spectrum auction with a dynamic supply and a log approximation to the optimal social welfare. To the best of our knowledge, we are the first to design truthful spectrum auctions enabling fair payments for homogenous channels and spectrum reusability with dynamic spectrum supply. Experimental results show that our schemes outperform the existing benchmarks by providing almost perfect fairness of pricing for both single-and multi-unit demand spectrum users.

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Truth revelation in approximately efficient combinatorial auctions

Cited by 175 publications

References 11 publications

AEGIS: An Unknown Combinatorial Auction Mechanism Framework for Heterogeneous Spectrum Redistribution in Noncooperative Wireless Networks

AEGIS: An Unknown Combinatorial Auction Mechanism Framework for Heterogeneous Spectrum Redistribution in Noncooperative Wireless Networks

eBay in the Clouds: False-Name-Proof Auctions for Cloud Resource Allocation

Fair Pricing in the Sky: Truthful Frequency Allocation with Dynamic Spectrum Supply

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