Truthful Double Auction Mechanism Research Articles

A Truthful Double Auction Mechanism for Multi-Resource Allocation in Crowd Sensing Systems

As a novel sensing paradigm, crowd sensing systems have gained great attention and been widely adopted in the environmental monitoring and calculation areas. In crowd sensing systems, mobile users provide their multiple resources to the requesters to execute tasks. Existing studies focus on the divisible task or one-to-one mapping for single resource allocation. However, this assumption does not hold for crowd sensing systems. Owing to the task attribute, some tasks cannot be divided into multiple parts to run on different devices. In addition, a high performance mobile device can execute multiple tasks simultaneously. We address the problem of multi-resource allocation in crowd sensing systems for the auction-based model considering many-to-one mapping for indivisible tasks, where many-to-one mapping allows one mobile device to provide multiple resources to execute one or more tasks. In this article, we study, for the first time to the best of our knowledge, a truthful mechanism that stimulates mobile users and requesters to declare their true values. We design a truthful double auction mechanism together with a payment scheme tailored to fit it that would help researchers understand how a truthful double auction mechanism can be designed. In addition, we prove that our proposed mechanism maintains budget-balance, individual rationality, and computational tractability. Furthermore, we analyze the approximation ratio of our proposed approximation algorithm. Experimental results demonstrate that our proposed mechanism has high computation efficiency and good performance.

PP-SPEC: Securing Spectrum Allocation for Internet of Things

The explosive growth of the Internet of Things (IoT) is posing a high pressure on the spectrum resources. Dynamic spectrum allocation is an effective solution for supporting massive IoT devices with limited spectrum resources, often implemented in the form of spectrum auction. Among diverse auction formats, double auctions feature multiple buyers and multiple sellers, which is applicable to a wide range of IoT scenarios. Nevertheless, the existing double auction mechanisms mostly focus on the design of truthfulness and ignore the importance of privacy preservation. Hence, in this article, we propose PP-SPEC, a truthful and privacy-preserving double auction mechanism that takes spatial reuse, spectrum heterogeneity, and multiminded bidders into account, and provides full privacy in terms of asking prices, bidding values, and locations. To tackle the challenge of privacy-preserving comparison over ciphertext field, we carefully designed a set of generic privacy-preserving ciphertext comparison protocols (PIC), including basic PIC (B-PIC) and extended PIC (E-PIC), by integrating additive homomorphic encryption and garbled circuits. Furthermore, we have theoretically proved the truthfulness and security of PP-SPEC. We have implemented and evaluated PP-SPEC, whose experimental results show high performance and practicability of PP-SPEC for real-life applications.

Double Auction for a Data Trading Market with Preferences and Conflicts of Interest

Abstract The advent of big data era has given rise to the big data trading market because of the potentially enormous economic value. However, designing an effective trading mechanism for the data trading market is still in its infancy. Existing several incentive mechanisms have neglected the important fact that data consumers have both preferences and complex conflicts of interest (CoI) relations among them. In response to the limitations of existing trading mechanisms, we propose DTPCI, a truthful double auction mechanism for a Data Trading market with two unique characteristics of consumers’ Preferences and complex CoI relations among them. However, three major challenges have to be addressed, i.e. diverse market preferences, the complex CoI relations of data consumers and the strategic behaviors of both two sides. To jointly address the three challenges, we propose DTPCI to achieve nonnegative social welfare, which features a group rule and a data trading rule. The group rule generates all conflict-free virtual groups based on the CoI graph. The data trading rule adopts the group buying to share data and expense. Through rigorous theoretical analysis and real-data based experiments, we demonstrate that DTPCI achieves all the desired economic properties.

Privacy-Preserving and Truthful Double Auction for Heterogeneous Spectrum

Over the past decades, there have been extensive research endeavors in spectrum auction design. However, most solutions only focus on the allocation efficiency while ignoring the privacy leakage inherent in the process of spectrum auction. So far, the very few existing works on secure spectrum auctions either provide inadequate privacy protection or incur performance loss in terms of spectrum reusability. In this paper, for the first time, we propose PS-TAHES, a privacy-preserving and truthful double auction mechanism for heterogeneous spectrum. PS-TAHES is constructed based on our carefully designed security primitives, which can support various arithmetics over encrypted data, including multiplication, bid comparison, and sorting matrix, and they are well applicable in other contexts. We theoretically analyze the security and efficiency of PS-TAHES, which is proved to ensure a full and strong privacy protection for bidders while preserving the allocation efficiency of the original auction mechanism. Experimental results, consistent with the theoretical analysis, further validate the practical use of PS-TAHES in real-world applications.

A Double Auction Mechanism to Bridge Users’ Task Requirements and Providers’ Resources in Two-Sided Cloud Markets

Double auction-based pricing model is an efficient pricing model to balance users’ and providers’ benefits. Existing double auction mechanisms usually require both users and providers to bid with the unit price and the number of VMs. However, in practice users seldom know the exact number of VMs that meets their task requirements, which leads to users’ task requirements inconsistent with providers’ resource. In this paper, we propose a truthful double auction mechanism, including a matching process as well as a pricing and VM allocation scheme, to bridge users’ task requirements and providers’ resources in two-sided cloud markets. In the matching process, we design a cost-aware resource algorithm based on Lyapunov optimization techniques to precisely obtain the number of VMs that meets users’ task requirements. In the pricing and VM allocation scheme, we apply the idea of second-price auction to determine the final price and the number of provisioned VMs in the double auction. We theoretically prove our proposed mechanism is individual-rational, truthful and budget-balanced, and analyze the optimality of proposed algorithm. Through simulation experiments, the results show that the individual profits achieved by our algorithm are 12.35 and 11.02 percent larger than that of scale-out and greedy scale-up algorithms respectively for 90 percent of users, and the social welfare of our mechanism is only 7.01 percent smaller than that of the optimum mechanism in the worst case.

Shared parking problem: A novel truthful double auction mechanism approach

Considering a parking platform with multiple slot demanders and multiple slot suppliers, this paper addresses two truthful double auction mechanisms for shared parking problem, where the demanders targeted by the proposed mechanisms are with flexible schedules and for non-work activities, and the suppliers are with the typical daily ‘driving go out early and come back at dusk’ pattern. To provide flexible match schemes and increase the trading scale, we allow “all-or-nothing” principle for demanders and “one-to-many” principle for suppliers. Based on the parking slot allocation rule and the transaction payment rule, we first relax the single output restriction (suppliers can only submit bids on a single unit of one commodity) and propose a “demander competition padding method (DC-PM)” auction mechanism, which is used to solve potential budget deficit. To avoid the likely distorted social welfare resulted by the DC-PM auction mechanism and to add budget surplus, we further modify the parking slot allocation rule and the transaction payment rule in the DC-PM auction mechanism, and propose a “modified demander competition padding method (MDC-PM)” auction mechanism. Three economical properties of both auction mechanisms, i.e. incentive compatibility, individual rationality and budget balance, are proved. Numerical experiments show that the proposed two auction mechanisms can realize asymptotic efficiency as both demanders and suppliers approach infinity. Moreover, the DC-PM auction mechanism is superior to the MDC-PM auction mechanism with respect to participants’ utilities and can maintain the strict lexicographic allocation order, and the MDC-PM auction mechanism outperforms the DC-PM auction mechanism in terms of welfare efficiency and platform's payoff. Issues of managerial implications for shared parking problem are further discussed in this paper.

A systematic study of double auction mechanisms in cloud computing

The cloud system is designed, implemented and conceptualized as a marketplace where resources are traded. This demands efficient allocation of resources to benefit both the cloud users and the cloud service providers. Accordingly, market based resource allocation models for cloud computing have been proposed. These models apply economy based approaches e.g. auction, negotiation etc. This work makes a detailed study of the double auction mechanisms and their applicability for the cloud markets. A framework for a future cloud market using double auction is also proposed. As most of the existing works in double auction confines only resource allocation, therefore, a Truthful Multi-Unit Double Auction mechanism (TMDA) is proposed that would help researchers to understand how a truthful double auction mechanism can be designed. TMDA is proven to be asymptotically efficient, individual rational, truthful and budget-balanced. TMDA would also encourage researchers to contribute in this emerging area. The performance of TMDA, which addresses the interests of both the cloud user and the provider, has been validated through simulation study. Various challenges in the realization of double auction mechanisms in cloud computing along-with the future possibilities are also presented.

Truthful double auction of spectrum trading for femtocell service provision

The femtocell has been considered as a promising technology to improve indoor mobile network coverage co-working with macrocell networks. However, lack of licensed spectrum limits the development of the femtocell service provision. A feasible solution is that a femtocell service provider (FSP) leases spectrum from the existing licensed spectrum holder, the macrocell service provider (MSP). Existing research focuses on the interaction between a single FSP and MSP. In this paper, we investigate a spectrum trading framework for multiple FSPs and MSPs. Under such a scenario, both FSPs and MSPs have to compete with their peers in the trading. To balance the revenue and the cost from the spectrum trading, an analysis is made on how to determine the acceptable spectrum trading prices and volumes for both MSPs and FSPs. To guarantee the fairness of the transaction, we introduce a truthful double auction mechanism for the spectrum trading between FSPs and MSPs, which compels them to report their bids or asks honestly according to their valuations. In particular, the truthfulness and other properties of the spectrum double auction have been proved. Finally, the numerical results illustrate how the acceptable spectrum trading prices and volumes are determined and also how the spectrum double auction mechanism works. Copyright © 2016 John Wiley & Sons, Ltd.

A truthful double auction for two-sided heterogeneous mobile crowdsensing markets

Incentive mechanisms are critical for the success of mobile crowdsensing (MCS). Existing mechanisms mainly focus on scenarios where all sensing tasks are belong to a monopolistic campaign, while ignoring the situation where multiple campaigns coexist and compete for potential sensing capacities. In this paper, we study mechanisms in a two-sided heterogeneous MCS market with multiple requesters and users, where each requester publishes a sensing campaign consisting of various tasks whereas each user can undertake multiple tasks from one or more campaigns. The mechanism design in such a market is very challenging as the demands and supplies are extremely diverse. To fairly and effectively allocate resources and facilitate trades, we propose a novel truthful double auction mechanism named TDMC. By introducing a carefully designed virtual padding requester, a two-stage allocation approach and corresponding pricing schemes for both requesters and users are developed in TDMC. Through theoretical analysis, we prove that TDMC has the properties of truthfulness, individual rationality, budget balance, computational tractability, and asymptotic efficiency as the workload supply compared with demand becomes more and more sufficient. To make TDMC more adaptable, we further introduce two more flexible bid profiles for both requesters and users, and two adjustment methods to control the sensing quality. Extensive simulations demonstrate the effectiveness of TDMC.

Game‐theoretic auction design for bandwidth sharing in helper‐assisted P2P streaming

SummaryVideo traffic offloading through the helper peers can significantly alleviate the server workload and enhance users' quality of experience. In this paper, the complex interactions of a number of helpers seeking to trade their bandwidth surplus in a peer‐to‐peer market are studied using non‐cooperative game theory and double auction. In particular, a non‐cooperative game is formulated among the helpers in which each helper can make a decision on the maximum amount of upload bandwidth surplus that it is willing to sell so as to maximize its utility function that reflects the tradeoff between the benefits from bandwidth sharing and its associated costs. Then, the price governing the bandwidth trading market between the helpers and peers is determined via a truthful double auction mechanism. To solve the game, an algorithm based on the best response dynamics is proposed using which helpers can reach a Nash equilibrium point. Simulation results exhibit that the proposed algorithm achieves significant performance improvements in terms of utility per selling helpers. Copyright © 2015 John Wiley & Sons, Ltd.

A Truthful Double Auction Mechanism for Hybrid Spectrums

Auctions have been widely studied as an efficient approach of allocating spectrum among secondary users in recent years. On the other side, a wide range of frequency bands could be available in a spectrum auction considering the current trend of deregulating wireless resources, therefore, channels provided by the primary users may reside in widely separated frequency bands, and due to the difference in propagation profile, would show significant heterogeneity in transmission range, channel error rate, path-loss, etc. Also, we can consider the channels with similar propagation and quality characteristics, for example, channels located in the same frequency band, are homogeneous and can be located in one spectrum type. Therefore, in this paper, we propose a double auction mechanism for both homogeneous and heterogeneous spectrums, called hybrid spectrums. The hybrid auction design has its own challenges, especially it also inherits the challenges related to heterogeneity. We prove that our auction design can not only solve the challenges caused by hybrid spectrums but also preserve three important economic aspects including truthfulness, budget balance and individual rationality. Also, we show that the proposed scheme increases spectrum utilization through spectrum reuse. Also, we offer a novel comprehensive grouping procedure to increase both the channel utilization and the seller satisfaction. Results from extensive simulation studies demonstrate good performance of the proposed algorithms on various auction metrics.

A Truthful Multi-Channel Double Auction Mechanism for Heterogeneous Spectrums

Auction has been widely used to spectrum allocation. Most of the previous works supposed that all the spectrum are identical. However, in reality, spectrums are quite different in different locatio...

TAHES: A Truthful Double Auction Mechanism for Heterogeneous Spectrums

Auction is widely applied in wireless communication for spectrum allocation. Most of prior works have assumed that all spectrums are identical. In reality, however, spectrums provided by different owners have distinctive characteristics in both spacial and frequency domains. Spectrum availability also varies in different geo-locations. Furthermore, frequency diversity may cause non-identical conflict relationships among spectrum buyers since different frequencies have distinct communication ranges. Under such a scenario, existing spectrum auction schemes cannot provide truthfulness or efficiency. In this paper, we propose a Truthful double Auction mechanism for HEterogeneous Spectrum, called TAHES, which allows buyers to explicitly express their personalized preferences for heterogeneous spectrums and also addresses the problem of interference graph variation. We prove that TAHES has nice economic properties including truthfulness, individual rationality and budget balance. Results from extensive simulation studies demonstrate the truthfulness, effectiveness and efficiency of TAHES.