Secure double spectrum auctions

In this paper, we investigate the problem of recall mechanism in a dynamic spectrum auction system. The licensed spectrum holders (SHs) can auction their idle channels to the secondary wireless service providers (SWSPs) for economic incentive. However, the primary user (PU) of an SH has higher priority than the SWSPs for the spectrum access. To deal with a sudden increase in PUs' spectrum demands after auction and guarantee their quality of services (QoS), we propose a Local recall-based dYnamic double spectRum auctIon meChanism (LYRIC) for SHs' spectrum auction operation. Different from the most existing approaches about spectrum recall-based spectrum auction, the proposed spectrum auction method for heterogeneous spectrum transaction takes account of the joint effect of heterogeneous demand, spectrum spatial reusability, and the economic efficiency. Simulation results show that the proposed LYRIC algorithm can improve the auction process of SHs, the channels utilization efficiency and the average buyers' satisfactory level with guarantees on the QoS of PUs.

In this paper, we investigate an online spectrum auction problem in cognitive radio networks with uncertain activities of primary users (PUs). In our framework, a primary base station (PBS), acted as the spectrum auctioneer, leases its under-utilized channels to secondary users (SUs) who request and access spectrum on the fly. Different from most of existing works in online spectrum allocation, we focus on a more practical situation that the auctioneer (or the PBS) has no prior knowledge of PUs' activities so that its channel states are not static. In order to balance the auction profits from granted SUs' spectrum requests and the potential penalties caused by incomplete services to PUs, we introduce the idea of virtual spectrum sellers and formulate the problem as an online double spectrum auction. We then propose a novel online admission and pricing mechanism which also considers the reusability of wireless spectrum. Theoretical analyses are provided to prove that our auction algorithm satisfies all desired economic properties in terms of budget-balance, individual rationality and truthfulness. Simulation results show that our proposed auction algorithm can increase the utility of the PBS, enhance spectrum utilization and achieve better satisfaction for SUs compared to counterparts.

In recent years, a large number of spectrum mechanisms have been proposed, but these mechanisms ignore the security issues that arise during the design of the mechanism. In this paper, two secure models for sealed-bid spectrum auction are given based on Wang’s generic spectrum auction mechanism. One is the basic model and another improved model based on the basic model is proposed, which maximizes Social welfare while it is a Privacy-preserving Spectrum auction mechanism with public Verification namely SPSV. The SPSV scheme achieves the properties of maximizing the social welfare but also, by using the double paillier cryptosystem, it is privacy-preserving for bidders’ bids without revealing any sensitive information to auctioneer or agent during the entire spectrum auction. Oblivious transfer is applied to ensure the anonymity of bidders. Furthermore, the use of inequality comparison proof also provides the public verification of winner group to verify the comparison relationship between winner groups and losing groups. At last, the performance analysis are given.

The concept of green payments together with single and multiple bidding processes for short-term spectrum auctions are compared based on two reference cases: (1) when the users and the auctioneer are aware of the value of the reserve price, and (2) when the value of the reserve price is known only to the auctioneer. This involves a novel concept known as the green payment. This concept is combined with the use of probabilities to determine the users participating in the auction process. The purpose of the green payment and the probability is to help in reducing the amount of energy wasted as a result of the auction process. The utility of each user and that of the wireless service provider with and without the green payment is also examined. The revenue obtained from each of the examined models is also compared to determine which model is more profitable for the WSP. This paper shows that the use of multiple bidding process for short-term spectrum auctions gives a better performance measure when compared to the single bidding process, more particularly when the value of the reserve price is known to the auctioneer and the users in the system. It also shows that using the proposed probability equation in combination with the concept of the green payment helps in reducing the amount of energy consumed by the system.

This paper examines an extended double auction model where market clearing is restricted by temporal constraints. It is found that the allocation problem in this model can be effectively transformed into a weighted bipartite matching in graph theory. By using the augmentation technique, we propose a Vickrey-Clarke-Groves (VCG) mechanism in this model and demonstrate the advantages of the payment compared with the classical VCG payment (the Clarke pivot payment). We also show that the algorithms for both allocation and payment calculation run in polynomial time. It is expected that the method and results provided in this paper can be applied to the design and analysis of dynamic double auctions and futures markets.

In order to fully utilize spectrum, auction-based dynamic spectrum access has become a promising approach which allows unlicensed wireless users to lease unused bands from spectrum license holders. Traditionally, the property of spectrum goes to a unique winner with the highest bid after the auction, and the bidders with low bids would be probably not served. This also may result in spectrum resource wasting when the assigned band is larger than the original request. In fact, because the spectrum is divisible goods, it can be shared among a group of users. In this paper, we propose a novel virtual bidder group (VBG) mechanism in spectrum auction which allows multiple winners to obtain the spectrum item simultaneously. Furthermore, a heuristic phase-optimization algorithm is proposed to reduce the crucial exponential computing time issue of band allocation optimization in double-side bandwidth auction scenario with multiple auctioneers. Simulation results prove that the VBG scheme could significantly improve the realized system data rate and the bandwidth utility, which indicates higher revenue for the spectrum license holder; meanwhile, the proposed phase-optimization algorithm exhibits relative low complexity and could provide a near-optimal performance.

Recently, Indian telecommunication industry has passed through an auction process of 3G spectrum, which has enabled the government to collect hefty license fees. The successful bidders are expected to borrow this bid amount from the commercial banks and repay from the revenue to be generated from the new services. This paper looks at this issue theoretically. The telecommunication firms operate on the basis of acquisition of airwave space, which is licensed by the government. The usual policy practice is to distribute the available spectrum by an ascending auction. As per the economic theory, auction has two merits. Firstly, auction ensures that spectrum goes to the most efficient firm, which is by definition the firm that makes the maximum profit among all. This firm by virtue of their maximum profit bids the highest amount in the auction and gets the spectrum. Secondly, spectrum auction ensures revenue maximization of the government. This result of efficiency optimization however holds under the assumption of perfect information and no uncertainty. Uncertainty and irrationality like over-optimism can lead to problems like ‘winners‘ curse' or ‘broke winners’ under auction. Still auction is market-based and less controversial than discretionary distribution. However, this paper argues that high amount of auction bid can result in several deficiencies in the telecom industry. An issue of debate is whether high auction bid will result in higher price for the services. Under the assumption of infinite time horizon, high license fee is a sunk cost and therefore does not raise price. But this paper shows that a high license fee can raise the lending bank�s interest charge for which not only price rises but the infrastructural investment in the telecom industry suffers. After the acquisition of spectrum through auction the industry needs infrastructural investments to roll out the quality services. Inadequate investment in infrastructural activities like procurement of quality equipments, erection of tower, etc., may result in lower quantum of services with degraded qualities. This is in fact a reality in India where not only rural telecom infrastructure is vastly inadequate, the urban telecom infrastructure is also under severe stress. In this paper, using the tool of game theory we show how capacity and quantity choice game of firms ends up in high auction bid and sub-optimal investment on infrastructure. Then how can the social planners simultaneously achieve the twin objective of growth and revenue maximization? The paper shows that these objectives are realized if a part of the license fee is spent for the subsidization of infrastructural investment in the telecom industry.

In dynamic spectrum auction, if a buyer locates in a "critical" place, interfering with many other buyers, its occupancy of the spectrum may deprive many others the transmission opportunity. In this paper, we for the first time propose a location-aware online double auction mechanism, LOTUS. The biggest challenge is: the spectrum requests are sporadic, an interference-harmful buyer may request spectrum earlier than others, making it difficult to decide whether to grant its spectrum request instantly. To address the challenge, we considers the opportunity cost of the spectrum allocation regarding location-based interference conditions. We introduce the "interference discount" to characterize the interference harmfulness. The simulation results show that LOTUS can improve buyers' utility by more than 110% over the static auction, and 25% over the online auction without considering interference discount. The spectrum utilization is enhanced by 120% over static auction, and 65.3% over the online auction without considering interference discount.

Online digital goods auctions are settings where a seller with an unlimited supply of goods (e.g. music or movie downloads) interacts with a stream of potential buyers. In the posted price setting, the seller makes a take-it-or-leave-it offer to each arriving buyer. We study the seller's revenue maximization problem in posted-price auctions of digital goods. We find that algorithms from the multi-armed bandit literature like UCB, which come with good regret bounds, can be slow to converge. We propose and study two alternatives: (1) a scheme based on using Gittins indices with priors that make appropriate use of domain knowledge; (2) a new learning algorithm, LLVD, that assumes a linear demand curve, and maintains a Beta prior over the free parameter using a moment-matching approximation. LLVD is not only (approximately) optimal for linear demand, but also learns fast and performs well when the linearity assumption is violated, for example in the cases of two natural valuation distributions, exponential and log-normal.

Task allocation has been widely studied in high-performance computing environment. However, existing task allocation algorithms can not be directly applied to WSN because of the limited energy resources and computing capabilities of the Wireless Sensor Network (WSN). In this paper, we propose a new auction-based task allocation model for WSN and create an energy consumption based utility function to evaluate the allocation plan. Moreover, new policies are added into traditional auction scheme. Simulation results show that the proposed improved auction mechanism of Multi-Agent System (MAS) auto-negotiation model is a real-time and effective scheme, which can be carried out to allocate tasks for WSN with a high success rate.

Extensive research in recent years has shown that dynamic spectrum sharing is a promising approach to address the artificial spectrum scarcity problem by improving spectrum utilization. This new communication paradigm, however, requires a well-designed spectrum allocation mechanism. This paper designs a double spectrum auction framework that allows unlicensed secondary users to obtain selected idle spectra assigned to licensed primary users. This is a win-win game because primary users can earn extra revenue and secondary users can obtain spectra they desperately need. The competition among primary users in the auction framework is studied combining game theory with a double spectrum auction in a non-cooperative game with the Nash Equilibrium (NE) as the best solution. Primary users use the prices obtained from the NE as their bid strategies to participate in the auction. In this auction sellers and buyers bid privately and confidentially, which means that the secondary users do not actually know the price and the spectrum size offered by the primary users, then a new net utility function was developed for the primary users with an iterative algorithm to find the Nash equilibrium point. Simulations demonstrate that this design effectively improves spectrum utilization.

Auction is an effective mechanism to distribute spectrum resources. Although many privacy-preserving auction schemes for spectrum allocation have been proposed, none of them is able to perform practical spectrum auctions while ensuring enough security for bidders' private information, such as geo-locations, bid values, and data access patterns. To address this problem, we propose SLISA, a lightweight auction framework which enables an efficient spectrum allocation without revealing anything but the auction outcome, i.e., the winning bidders and their clearing prices. We present contributions on two fronts. First, as a foundation of our design, we adopt a Shuffle-then-Compute strategy to build a series of secure sub-protocols based on lightweight cryptographic primitives (e.g., additive secret sharing and basic garbled circuits). Second, we improve an advanced spectrum auction mechanism to make it data-oblivious, such that data access patterns can be hidden. Meanwhile, the modified protocols adapt to our elaborate building blocks without affecting its validity and security. We formally prove the security of all protocols under a semi-honest adversary model, and demonstrate performance improvements compared with state-of-the-art works through extensive experiments.

In this paper, competition among multiple secondary users (SUs) for spectrum access is modeled as a simultaneous repeated auction. Upon participation in an auction, a SU is charged with an entry fee. However, participation does not ensure an access to the channel. This tradeoff leads it to decide either for or against entering the auction. We consider no cooperation among the SUs, and model this situation as a Bayesian game. A modification of the standard regret testing procedure is proposed to fit our system model. Our proposed procedure converges to Nash equilibrium (NE) of the game. Since this procedure is computationally expensive, we propose a less expensive learning based procedure for the decision taking. We present computer simulation results to compare the average profits and bidding efficiencies over time for the proposed procedure. We also compare their bidding efficiencies to another procedure in the literature, based on second highest bid prediction.

With the proliferation of retail commerce on the Internet, mobile agents play more and more important roles in automating information brokering and negoiation for online shopping. However, due to the limited computing resources and security concerns, current first-generation shopping agents have limited capacities to conduct commercial bargaining. On the other hand, though auctions appear promising to solve these dificulties with their fairness and openness features, they suffer from the problems such as reversed consumer-buyer relation and low performance. In this paper, we propose a secure agent-mediated auction-like negotiation protocol which combines togather the favorable features of traditional English auction and mobile agent scheme. Its features lie at: (1) auctionlike scheme is implemented which keeps the dominant equilibrium in the English auction and rationalizes consumer-seller relation in the retail commerce. (2) security for negotiation agents is guaranteed which makes tampering on agent body easy to detect. (3) flexibility during the trading is achieved by combining information gathering and negotiation together while few communications are needed.

In this research, we present an auction-inspired model for providing/demanding resources without any money exchange among cloud service providers. This model, which we call Bartering Double Auction Resource Allocation (BDARA), helps service providers receive the resources they need in the form of virtual machines with different types of functionality. Under this mechanism, if one party violates the SLA, the other one takes back its resources to avoid possible loss. The experimental results using the CloudSim simulator as well as the statistical analyses show that the proposed mechanism can increase the social welfare and profitability of service providers while significantly reducing SLA violations.