Combinatorial double-sided auctions for network bandwidth allocation: a budget-balanced and decentralized approach

Telecommunication networks are now an interconnection of competitive operators that need to cooperate to ensure end-to-end delivery of traffic. Inter-domain agreements have to be performed, and pricing is seen as a relevant way to reward intermediate domains for forwarding the traffic of others. In previous works, Vickrey–Clark–Groves (VCG) double-sided auctions have been applied because they provide proper incentives, lead to an efficient use of the network, and verify other relevant characteristics. However, it has been highlighted that the resource allocation schemes applying VCG auction are neither budget-balanced nor solvable in a decentralized way. In this paper, we apply combinatorial double-sided auction to allocate the bandwidth resources over nodes. While previous works were using a centralized algorithm, we use here a new pricing rule, leading to a new budget-balanced pricing scheme for which allocations and charges can be computed in a decentralized way. We also analyze the impact of this scheme on the game over declared costs of nodes.     

基于在线拍卖的网络切片资源分配算法

为满足未来移动通信网络中多样化的业务需求,为用户提供定制化服务的同时提升网络经济效益,该文提出一种基于在线拍卖的网络切片资源分配算法。根据业务类型将用户的服务请求转化为相应投标信息,以最大化拍卖参与者的社会福利为目标,将切片资源分配问题建模为基于多业务的在线赢家确定问题。结合资源分配与价格更新策略,实现基于在线拍卖的资源优化配置。仿真结果表明,该算法能够在满足用户业务需求的同时,提升网络经济效益。     

Ad Hoc网络中基于双向拍卖的协作激励机制

文章把双向拍卖机制引入到Ad Hoc网络中,并给出了两种不同的以双向拍卖为基础的协作激励机制。一种是基于路径的双向拍卖,通过路径的费用集合同各目的节点所提供的竞价进行双向拍卖。另一种则是基于邻居节点的双向拍卖,通过一系列的本地双向拍卖,逐一确定路径的节点,以致形成通讯的路径。理论分析表明,这种机制能够促使各节点相互协作,达到形成通讯路径的目的。     

Resource planning and incentive engineering for a congested wireless access point: an integrated multiple time scale control mechanism

Wireless networks are playing an increasingly important role for global communications. Many resource allocation mechanisms have been proposed to efficiently utilize the limited radio resources in wireless networks to support a large number of mobile users with a diversity of applications. Among them, pricing frameworks that provide incentives to users to maximize their individual utility while optimizing allocation of network resources have attracted a lot of attention recently. Nevertheless, most of these pricing schemes require dynamic charging rates and may be too complex for wide acceptance by users, as most users would prefer relatively simple charging schemes. Moreover, use of a pricing framework to facilitate resource planning and future expansion at the service provider’s side has not yet been widely considered. In this paper, we propose Integrated Multiple Time Scale Control (IMTSC), a novel incentive engineering mechanism to facilitate resource allocation and network planning. Over different time scales, IMTSC combines the functions of network capacity planning, admission control for resource allocation, and tracking of users’ instantaneous traffic demands. The proposed mechanism is applied for access control at a congested access point in a wireless network. By decomposing the original problem into distributed optimization problems that are solved locally by the service provider through adjusting charging rate and remotely by individual users by appropriately changing her service requests, we show that maximization of user’s utility and increase of network efficiency can be simultaneously achieved. Results from extensive simulations demonstrate the effectiveness of the proposed IMTSC mechanism.     

Repeat Bidding on Internet-Based Multiple-Item “Name-Your-Own-Price” Auctions

Name-Your-Own-Price (NYOP) auctions have gained recent popularity on the Internet. In many NYOP settings, the auction firm displays multiple bidding items for the bidders (such as multiple options of airline tickets) and restricts them to place a single offer. Recent studies have, however, shown that the Internet environment enables many customers to engage in repeat bidding. Our purpose in this paper is: 1) to analyze the consumer value gained by repeat bidding on multiple-item NYOP auctions under different-bidding strategies; 2) to derive an upper bound on the value gained by repeat bidding when multiple items are present; and 3) to analyze the multiple-item NYOP auction from a consumer-firm perspective. We use Monte Carlo simulation to discuss the effects of various auction parameters on the firm's expected profit, and show that the presence of multiple bidding items provides a win–win situation for both the auction firm and the bidders. In particular, we show that multiple items increase the expected value for the consumers and also help firms mitigate potential losses due to repeat bidding.      

Privacy-preserving multi-attribute reverse spectrum auction scheme

Aiming the problem that the existing reverse spectrum auctions do not take the non-price attribute of spectrum into account and the security of spectrum auction,a privacy-preserving multi-attribute reverse spectrum auction was proposed.Firstly,price and non-price positive attributes of spectrum were considered as the bidding scheme of bidders and auctions was performed to judge spectrum winners.Secondly,to ensure the security of the spectrum auction,the Paillier threshold system was used to introduce a group of spectrum auction servers of auctioneers to replace the traditional single third-party agency,which could prevent the fraud collusion between spectrum auctioneers and bidders.The cryptography tools such as the anonymization technology and oblivious transfer were introduced to achieve the secure features,which could make the spectrum auction performed securely.The security analysis shows that the security protocol has strong security.The performance of the protocol is also evaluated,and experimental results show that the security scheme is superior to the multi-attribute reverse auction security scheme that can be applied in the spectrum auction scenario in terms of computational overhead.     

A Bidding Algorithm for Optimized Utility-Based Resource Allocation in Ad Hoc Networks

This article proposes a scheme for bandwidth allocation in wireless ad hoc networks. The quality of service (QoS) levels for each end-to-end flow are expressed using resource-utility functions, and our algorithms aim to maximize aggregated utility. The shared channel is modeled as bandwidth resources defined by maximal cliques of mutual interfering links. We propose an entirely novel resource allocation algorithm that employs auction mechanisms where flows are bidding for resources. The bids depend both on the flow's utility function and the intrinsically derived shadow prices. Then we combine it with a utility-aware on-demand shortest path routing algorithm where shadow prices are used as a natural distance metric. We also show that the problem can be formulated as a linear programming problem. Thus we can compare the performance of our scheme to the centralized optimal LP solution, registering results very close to the optimum. We isolate the performance of the price-based routing and show its advantages in hotspot scenarios, and also propose an asynchronous version that is more feasible for ad hoc environments. Experimental results of a comparison with the state-of-the-art approach based on Kelly's utility maximization framework show that our approach exhibits superior performance for networks with both increased mobility or increased allocation period.     

Auction-Based Resource Allocation for Cooperative Communications

Distributed and efficient resource allocation is critical for fully realizing the benefits of cooperative communications in large scale communication networks. This paper proposes two auction mechanisms, the SNR auction and the power auction, that determine relay selection and relay power allocation in a distributed fashion. A single-relay network is considered first, and the existence and uniqueness of the Nash Equilibrium (i.e., the auction?s outcome) are proved. It is shown that the power auction achieves the efficient allocation by maximizing the total rate increase, and the SNR auction is flexible in trading off fairness and efficiency. For both auctions, the distributed best response bid updates globally converge to the unique Nash Equilibrium in a completely asynchronous manner. The analysis is then generalized to networks with multiple relays, and the existence of the Nash Equilibrium is shown under appropriate conditions. Simulation results verify the effectiveness and robustness of the proposed algorithms.     

A secure spectrum auction scheme without the trusted party based on the smart contract

With the development of communication 5G networks and technologies, spectrum resources are increasingly scarce. The scarcity of the spectrum resource makes market-driven spectrum auction become an important means of spectrum allocation, and due to the complexity of the network environment, the security of spectrum auctions can not be ignored. Most existing secure spectrum auction schemes introduce a semi-honest agent to complete spectrum auction. However, the hypothetical semi-honest model does not guarantee the security of spectrum auction in the actual application scenario, which may lead to potential security threats: the agent may reveal the privacy of bidders, agent or auctioneer may collude with the bidder to manipulate the spectrum auction, and so on. In this paper, a secure spectrum auction scheme without a trusted party is proposed based on the smart contract technology, and the smart contract written into the blockchain replaces the traditional semi-honest agent to cooperate with the auctioneer server to complete the auction. In order to ensure the security of our scheme, a secure spectrum auction protocol is designed, in which the Software Guard Extensions (SGX) technology and Paillier cryptosystem are used to protect the privacy of bidders. Public verification is provided in our protocol by using extensive Pedersen commitment, which prevents the auctioneer server and the bidder from colluding with each other and verifies group bid sum values. Finally, the security analysis is given to propose several types of attacks that can be defended. Besides, theoretical analysis and simulation experiments of our protocol are also provided.     

Stochastic Traffic Engineering in Multihop Cognitive Wireless Mesh Networks

In this work, the stochastic traffic engineering problem in multihop cognitive wireless mesh networks is addressed. The challenges induced by the random behaviors of the primary users are investigated in a stochastic network utility maximization framework. For the convex stochastic traffic engineering problem, we propose a fully distributed algorithmic solution which provably converges to the global optimum with probability one. We next extend our framework to the cognitive wireless mesh networks with nonconvex utility functions, where a decentralized algorithmic solution, based on learning automata techniques, is proposed. We show that the decentralized solution converges to the global optimum solution asymptotically.     

Spectrum auction with interference constraint for cognitive radio networks with multiple primary and secondary users

Extensive research in recent years has shown the benefits of cognitive radio technologies to improve the flexibility and efficiency of spectrum utilization. This new communication paradigm, however, requires a well-designed spectrum allocation mechanism. In this paper, we propose an auction framework for cognitive radio networks to allow unlicensed secondary users (SUs) to share the available spectrum of licensed primary users (PUs) fairly and efficiently, subject to the interference temperature constraint at each PU. To study the competition among SUs, we formulate a non-cooperative multiple-PU multiple-SU auction game and study the structure of the resulting equilibrium by solving a non-continuous two-dimensional optimization problem, including the existence, uniqueness of the equilibrium and the convergence to the equilibrium in the two auctions. A distributed algorithm is developed in which each SU updates its strategy based on local information to converge to the equilibrium. We also analyze the revenue allocation among PUs and propose an algorithm to set the prices under the guideline that the revenue of each PU should be proportional to its resource. We then extend the proposed auction framework to the more challenging scenario with free spectrum bands. We develop an algorithm based on the no-regret learning to reach a correlated equilibrium of the auction game. The proposed algorithm, which can be implemented distributedly based on local observation, is especially suited in decentralized adaptive learning environments as cognitive radio networks. Finally, through numerical experiments, we demonstrate the effectiveness of the proposed auction framework in achieving high efficiency and fairness in spectrum allocation.     

On spectrum allocation in cognitive radio networks: a double auction-based methodology

Auction is often applied in cognitive radio networks due to its efficiency and fairness properties. An important issue in designing an auction mechanism is how to utilize the limited spectrum resource in an efficient manner. In order to achieve this goal, we propose a predictive double spectrum auction model in this paper. Our auction model first obtains the bidding range from statistical analysis, and then separates the interval into independent states and employees a Markovian prediction based algorithm to generate guidelines for the bidding range of primary and secondary users, respectively. Comparing with existing approaches, our proposed auction model is more efficient in spectrum utilization and satisfies the economic properties. Extensive simulation results show that our work achieves an utilization ratio up to 91 %.     

Efficient signal proportional allocation (ESPA) mechanisms: decentralized social welfare maximization for divisible resources

We address the problem of devising efficient decentralized allocation mechanisms for a divisible resource, which is critical to many technological domains such as traffic management on the Internet and bandwidth allocation to agents in ad hoc wireless networks. We introduce a class of efficient signal proportional allocation (ESPA) mechanisms that yields an allocation which maximizes social welfare with minimal signaling and computational requirements for the resource. Revenue limits for this class are obtained and a sequence of schemes that approach these limits arbitrarily closely are given. We also present a locally stable negotiation scheme applicable to the entire class and illustrate efficiency and revenue properties through simulation.     

Auction-Based Effective Bandwidth Allocation Mechanism

Several auctions have been proposed and applied to perform contract negotiation and resource allocation in reservation-based networks. The methods proposed by these works perceive resources as single items with multiple units and place importance on a limited efficiency inside each node. However, as a user evaluates resources not individually, but rather as a whole set of required resources, the economical efficiency of the overall network cannot be achieved by these methods. To solve this problem, we propose a bandwidth allocation system using GVA (Generalised Vickrey Auction). Network resources, which are composed of many links at various bandwidths, are regarded by the proposed method as multiple items with multiple units. We describe how to apply GVA protocol to bandwidth allocations among multiple users. We investigate algorithmic and accounting problems inside multiple nodes using an end-to-end approach. We evaluate the proposed method's performance from various viewpoints: the utilisation of resources, profits of the telecommunications carriers, users' utility and users' satisfaction. We show that, by adopting GVA, the total utility of users can be maximised and the revenues of networks can also be improved.     

Spectrum redistribution for cognitive radios using discriminatory spectrum double auction

With the reformation of spectrum policy and the development of cognitive radio, secondary users will be allowed to access spectrums licensed to primary users. Spectrum auctions can facilitate this secondary spectrum access in a market‐driven way. To design an efficient auction framework, we first study the supply and demand pressures and the competitive equilibrium of the secondary spectrum market, considering the spectrum reusability. In well‐designed auctions, competition among participants should lead to the competitive equilibrium according to the traditional economic point of view. Then, a discriminatory price spectrum double auction framework is proposed for this market. In this framework, rational participants compete with each other by using bidding prices, and their profits are guaranteed to be non‐negative. A near‐optimal heuristic algorithm is also proposed to solve the auction clearing problem of the proposed framework efficiently. Experimental results verify the efficiency of the proposed auction clearing algorithm and demonstrate that competition among secondary users and primary users can lead to the competitive equilibrium during auction iterations using the proposed auction framework. Copyright © 2011 John Wiley & Sons, Ltd.     

Behavior modeling for spectrum sharing in wireless cognitive networks

Cognitive networks are designed based on the concept of dynamic and intelligent network management, characterizing the feature of self-sensing, self-configuration, self-learning, self-consciousness etc. In this paper, focusing on the spectrum sharing and competition, we propose a novel OODA (Orient-Observe-Decide-Act) based behavior modeling methodology to illustrate spectrum access problem in the heterogenous cognitive network which consists of multiple primary networks (PN, i.e. licensed networks) and multiple secondary networks (SN, i.e. unlicensed networks). Two different utility functions are designed for primary users and secondary users respectively based on marketing mechanism to formulate the decide module mathematically. Also, we adopt expectation and learning process in the utility design which considers the variance of channels, transmission forecasting, afore trading histories and etc. A double auction based spectrum trading scheme is established and implemented in two scenarios assorted from the supply-and-demand relationship i.e. LPMS (Less PNs and More SNs) and MPLS (More PNs and Less SNs). After the discussion of the Bayesian Nash Equilibrium, numerical results with four bidding strategies of SNs are presented to reinforce the effectiveness of the proposed utility evaluation based decision modules under two scenarios. Besides, we prove that the proposed behavior model based spectrum access method maintains frequency efficiency comparable with traditional centralized cognitive access approaches and reduces the network deployment cost.     

Cooperative bridge bidding (Corresp.)

A strategy is given for cooperative bidding by the players which results in the location of all 52 cards being encoded into a valid bridge auction which always terminates with a contract of six diamonds. Strategies are also given for encoding the card locations into auctions in which "double" and/or "redouble" are prohibited bids.     

3-G wireless auctions as an economic barrier to entry: the western european experience

Existing wireless telephony and messaging applications have the potential of being enhanced by broadband applications supported through “third generation” wireless services. Across the globe, governments have been allocating electro-magnetic spectrum for these 3-G services through an auction process. The rationale being that the entity that pays the most for a resource will create the greatest value from it. The use of auctions has removed the concept of public ownership of the electro-magnetic spectrum and radically redefined performance for this local communications technology. Issues of universal service, equality, and general definitions of performance and service characteristics are no longer directly addressed, but rather, service and performance are driven by marketplace competition. This paper theorizes that national and transnational wireless carriers acted to create barriers to new competition through the 3-G auctions by implementing a “win at any cost” strategy then retarding the roll-out of services and subsequently negotiating down the costs of the auction. In testing this perspective, the allocation and implementation of 3-G services in Western Europe are used as a case study. Analyses of the auction prices for 3-G licenses are compared to the intrinsic value of these licenses based upon a discounted cash flow model. These analyses demonstrate that prices paid for spectrum were uneconomic decisions. That is, economically speaking, these carriers overpaid for the spectrum. Further the actions by these carriers subsequent to the auction are analyzed to show that by retarding the introduction of 3-G services they continue to maximize revenues from existing wireless systems while they attempt to renegotiate auction terms and seek other types of regulatory relief.     

射频能量捕获传感网移动能量源的布置策略研究

射频能量捕获传感网（RF Energy Harvesting Wireless Sensor Network,RFEH-WSN）由专用射频能量源设备（Energy Transmitter,ET）和具有射频能量捕获功能的传感器节点（Energy Harvesting Recevier,简称EHR）组成.该网络解决了传感器网络中电池不易更换与节点能量容易耗尽的问题,使得RFEH-WSN应用前景更加广阔.RFEH-WSN应用中一个值得研究的问题是如何布置ET的充电位置,降低ET能耗且提高覆盖率.已有的工作主要考虑ET布置中单目标优化问题,如最小充电时间、最小功耗、最大覆盖率等.本文以时间最小和覆盖率最大为目标建立多目标优化模型,并提出利用粒子群算法（Particle Swarm Optimization,PSO）求解多目标函数（Multiple Object Program,MOP）的低复杂度近似算法,获得了最优Pareto解集.仿真结果表明,多目标优化可以满足不同情况的需求,提高充电效用.     

Distributed Scheduling and Dynamic Pricing in a Communication Network

This paper studies dynamic resource allocation in a decentralized communication network. The temporal aspect in the decentralized resource allocation problem presents new challenges, e.g., in optimizing the delay-throughput trade-off under user-specific delay costs. A dynamic bandwidth allocation game modelling an agent-based network is presented. The dynamic noncooperative game achieves Pareto-efficient bandwidth allocation that can be implemented by a greedy algorithm with pricing. Optimal dynamic pricing is discussed for the efficient sharing of network resources. An ad hoc wireless network is an example of such self-organizing decentralized system: the mobile nodes need not be directly connected to a base station. Another application of the model is to consider distributed uplink scheduling, based on local information, in a WCDMA network. The discretized control variable of a mobile node is either the received power/QoS-level or the binary decision on packet transmission.