Strategy-proof Auction Mechanisms Research Articles

A strategy-proof auction mechanism for service composition based on user preferences

A strategy-proof auction mechanism for service composition based on user preferences

Strategyproof auction mechanisms for network procurement

Deferred-acceptance auctions can be seen as heuristic algorithms to solve {{mathcal {N}}}{{mathcal {P}}}-hard allocation problems. Such auctions have been used in the context of the Incentive Auction by the US Federal Communications Commission in 2017, and they have remarkable incentive properties. Besides being strategyproof, they also prevent collusion among participants. Unfortunately, the worst-case approximation ratio of these algorithms is very low in general, but it was observed that they lead to near-optimal solutions in experiments on the specific allocation problem of the Incentive Auction. In this work, which is inspired by the telecommunications industry, we focus on a strategic version of the minimum Steiner tree problem, where the edges are owned by bidders with private costs. We design several deferred-acceptance auctions (DAAs) and compare their performance to the Vickrey–Clarke–Groves (VCG) mechanism as well as several other approximation mechanisms. We observe that, even for medium-sized inputs, the VCG mechanisms experiences impractical runtimes and that the DAAs match the approximation ratios of even the best strategy-proof mechanisms in the average case. We thus provide another example of an important practical mechanism design problem, where empirics suggest that carefully designed deferred-acceptance auctions with their superior incentive properties need not come at a cost in terms of allocative efficiency. Our experiments provide insights into the trade-off between solution quality and runtime and into the additional premium to be paid in DAAs to gain weak group-strategyproofness rather than just strategyproofness.

Privacy-preserving strategyproof auction mechanisms for resource allocation

Privacy-preserving strategyproof auction mechanisms for resource allocation

A Strategy-Proof Auction Mechanism for Adaptive-Width Channel Allocation in Wireless Networks

Efficient wireless channel allocation is becoming a more and more important topic in wireless networking. Dynamic channel allocation is believed to be an effective way to cope with the shortage of wireless channel resource. Up to now, a number of auction mechanisms have been designed to solve the problem of dynamic channel redistribution. Such designs deal with either the problem of single channel allocation or the problem of multiple channels allocation with an assumption of the same per-channel valuation. However, considering the recent outcomes of researches on throughputs of adaptive-width channels and the needs of wireless users in practice, we need to provide buyers with a way to submit various combinatorial bids for channels. This motivates our work on designing a more practical auction mechanism to solve the problem of channel redistribution. In this paper, we propose SPECIAL, which is a Strategy-Proof and EffiCIent multi-channel Auction mechanism for wireLess networks. SPECIAL guarantees the strategy proofness of the channel auction, exploits wireless channels’ spatial reusability, and achieves high channel allocation efficiency. Numerical results demonstrate that SPECIAL prevents buyers from manipulating the auction, and achieves high performance.

A General Privacy-Preserving Auction Mechanism for Secondary Spectrum Markets

Auctions are among the best-known market-based tools to solve the problem of dynamic spectrum redistribution. In recent years, a good number of strategy-proof auction mechanisms have been proposed to improve spectrum utilization and to prevent market manipulation. However, the issue of privacy preservation in spectrum auctions remains open. On the one hand, truthful bidding reveals bidders' private valuations of the spectrum. On the other hand, coverage/interference areas of the bidders may be revealed to determine conflicts. In this paper, we present PISA, which is a PrIvacy preserving and Strategy-proof Auction mechanism for spectrum allocation. PISA provides protection for both bid privacy and coverage/interference area privacy leveraging a privacy-preserving integer comparison protocol, which is well applicable in other contexts. We not only theoretically prove the privacy-preserving properties of PISA, but also extensively evaluate its performance. Evaluation results show that PISA achieves good spectrum allocation efficiency with light computation and communication overheads.

Towards Privacy Preservation in Strategy-Proof Spectrum Auction Mechanisms for Noncooperative Wireless Networks

The problem of dynamic spectrum redistribution has been extensively studied in recent years. Auctions are believed to be among the most effective tools to solve this problem. A great number of strategy-proof auction mechanisms have been proposed to improve spectrum allocation efficiency by stimulating bidders to truthfully reveal their valuations of spectrum, which are the private information of bidders. However, none of these approaches protects bidders' privacy. In this paper, we present PRIDE, which is a PRIvacy-preserving anD stratEgy-proof spectrum auction mechanism. PRIDE guarantees $k$ -anonymity for both single- and multiple-channel auctions. Furthermore, we enhance PRIDE to provide $\ell $ -diversity, which is an even stronger privacy protection than $k$ -anonymity. We not only rigorously prove the economic and privacy-preserving properties of PRIDE, but also extensively evaluate its performance. Our evaluation results show that PRIDE achieves good spectrum redistribution efficiency and fairness with low overhead.

A Strategy-Proof Combinatorial Heterogeneous Channel Auction Framework in Noncooperative Wireless Networks

Auction is believed to be an effective way to solve or relieve the problem of radio spectrum shortage, by dynamically redistributing idle wireless channels of primary users to secondary users. However, to design a practical channel auction mechanism, we have to consider five challenges, including strategy-proofness, channel spatial reusability, channel heterogeneity, bid diversity, and social welfare maximization. Unfortunately, none of the existing works fully considered the five design challenges. In this paper, we present the first in-depth study on the problem of dynamic channel redistribution jointly considering the five design challenges, and present SMASHER, which is a family of Strategy-proof coMbinatorial Auction mechaniSms for HEterogeneous channel Redistribution. SMASHER contains two strategy-proof auction mechanisms, namely SMASHER-AP and SMASHER-GR. SMASHER-AP is a strategy-proof, approximately efficient combinatorial auction mechanism for indivisible channel redistribution. We further consider the case, in which channels can be shared by the users in a paradigm of time-division multiplexing and propose SMASHER-GR, which is a strategy-proof channel allocation and scheduling mechanism. We have extensively evaluated our designs. The evaluation results show that our designs achieve much better performance than existing works.

PPS: Privacy-Preserving Strategyproof Social-Efficient Spectrum Auction Mechanisms

Many spectrum auction mechanisms have been proposed for spectrum allocation problem, and unfortunately, few of them protect the bid privacy of bidders and achieve good social efficiency. In this paper, we propose PPS, a Privacy Preserving Strategyproof spectrum auction framework. We design two schemes based on PPS separately for 1) the single-unit auction model (SUA), where only single channel will be sold in the spectrum market; and 2) the multi-unit auction model (MUA), where the primary user subleases multi-unit channels to the secondary users and each of the secondary users wants to access multi-unit channels either. Since the social efficiency maximization problem is NP-hard in both auction models, we present allocation mechanisms with approximation factors of (1 + ε) and 32 separately for SUA and MUA, and further judiciously design strategyproof auction mechanisms with privacy preserving based on them. Our extensive evaluations show that our mechanisms achieve good social efficiency and with low computation and communication overhead.