A sustainable and collaborative strategy for dynamic spectrum management in next generation wireless networks

Next generation wireless technologies offer various services from voice call to full motion pictures and even to high speed internet access. Consequently, the service providers (SP) armed with different wireless technologies (like 2.5G/3G/LTE) would require an adequate and significant amount of spectrum bandwidth for satisfying the need of their customers. Hence to achieve complete commercialization, the SPs, operating simultaneously, would demand for more and more spectrum from the regulatory body of the country. The spectrum demand on the part of the SP may vary with time (dynamic) because of varied kind of loads which are generated depending on the nature of the client-base, their requirements and their expected quality of experience. This work has addressed this challenging issue of allocating spectrum dynamically to different technologies under the portfolio of an SP. Here, we have conceived a scenario where service providers (SP) own multiple access networks (ANs) of different technologies. We envisage that an entity, called local spectrum controller (LSC) which is dedicated for managing the common pool of spectrum allocated to each SP. LSC is mainly responsible for distributing the spectrum to individual ANs of an SP in a fair manner. Since the available spectrum may not be sufficient enough to satisfy the aggregate demand from all ANs simultaneously, an LSC may face a situation, where satisfying individual demands from all ANs may result in a compromise between the demand and supply. This demand–supply situation would force an LSC or an SP to adhere to some dynamic spectrum management strategy, where demands of an AN would have to be satisfied depending on the current state of available spectrum and required usage of it. This calls for an adaptive dynamic strategy to be introduced by an SP for efficient spectrum distribution. The dynamic disparity of spectrum allocation can be idealized as a game between LSC and ANs. Hence, in the present work, we have modeled the problem of dynamic spectrum allocation as an n-player cooperative bankruptcy game and have solved the problem with the help of Shapley value and τ-value separately. We have investigated whether the ANs find it beneficial to cooperate with each other to make the solution sustainable enough. To evaluate the performances of the games that the ANs play, we have designed a novel utility function for each AN. We have identified plausible aims of an SP as minimizing overall dissatisfaction (MOD) and maximizing equality of distribution (MED). Next, we have studied performances of the above two solution concepts against max–min fairness algorithm (benchmarked in our case) with respect to the above objectives of LSC. Finally, we have proposed a unique heuristic in order to facilitate the decision making process of dynamic spectrum allocation, which leads to an adaptive yet optimized spectrum allocation strategy.     

Cooperative load balancing in distributed systems

A serious difficulty in concurrent programming of a distributed system is how to deal with scheduling and load balancing of such a system which may consist of heterogeneous computers. In this paper, we formulate the static load‐balancing problem in single class job distributed systems as a cooperative game among computers. The computers comprising the distributed system are modeled as M/M/1 queueing systems. It is shown that the Nash bargaining solution (NBS) provides an optimal solution (operation point) for the distributed system and it is also a fair solution. We propose a cooperative load‐balancing game and present the structure of NBS. For this game an algorithm for computing NBS is derived. We show that the fairness index is always equal to 1 using NBS, which means that the solution is fair to all jobs. Finally, the performance of our cooperative load‐balancing scheme is compared with that of other existing schemes. Copyright © 2008 John Wiley & Sons, Ltd.     

Energy-efficient power allocation for selfish cooperative communication networks using bargaining game

In commercial networks,user nodes operating on batteries are assumed to be selfish to consume their energy solely to maximize their own benefits,e.g.,data rates.In this paper,we propose a bargaining game to perform the power allocation for the selfish cooperative communication networks.In our system,two partner nodes can act as a source as well as a relay for each other,and each node is with an energy constraint to transmit one frame.Consider a selfish node is willing to seek cooperative transmission only if the data rate achieved through cooperation will not lower than that achieved through noncooperation by using the same amount of energy.The energy-efficient power allocation problem can be modeled as a cooperative game.We proved that there exists a unique Nash bargaining solution (NBS) for the game by verifying that the game is indeed a bargaining problem.Thus,the two objectives,i.e.,system efficiency and user fairness specified in the selfish networks can be achieved.Simulation results show that the NBS scheme is efficient in that the performance loss of the NBS scheme to that of the maximal overall rate scheme is small while the maximal-rate scheme is unfair.The simulation results also show that the NBS result is fair in that both nodes could experience better performance than they work independently and the degree of cooperation of a node only depends on how much contribution its partner can make to improve its own performance.     

Bargaining game theoretic power control in selfish cooperative relay networks

Wireless cooperative communications require appropriate power allocation (PA) between the source and relay nodes. In selfish cooperative communication networks, two partner user nodes could help relaying information for each other, but each user node has the incentive to consume his power solely to decrease its own symbol error rate (SER) at the receiver. In this paper, we propose a fair and efficient PA scheme for the decode-and-forward cooperation protocol in selfish cooperative relay networks. We formulate this PA problem as a two-user cooperative bargaining game, and use Nash bargaining solution (NBS) to achieve a win-win strategy for both partner users. Simulation results indicate that the NBS is fair in that the degree of cooperation of a user only depends on how much contribution its partner can make to decrease its SER at the receiver, and efficient in the sense that the SER performance of both users could be improved through the game.     

Game Theoretic subcarrier and power allocation for wireless OFDMA networks

This paper proposes a bargaining game theoretic resource(including the subcarrier and the power) allocation scheme for wireless orthogonal frequency division multiple access(OFDMA) networks.We define a wireless user s payoff as a function of the achieved data-rate.The fairness resource allocation problem can then be modeled as a cooperative bargaining game.The objective of the game is to maximize the aggregate payoffs for the users.To search for the Nash bargaining solution(NBS) of the game,a suboptimal subcarrier allocation is performed by assuming an equal power allocation.Thereafter,an optimal power allocation is performed to maximize the sum payoff for the users.By comparing with the max-rate and the max-min algorithms,simulation results show that the proposed game could achieve a good tradeoff between the user fairness and the overall system performance.     

Dynamic task assignment and resource management in cloud services by using bargaining solution

Cloud computing provides infrastructure, platform and software as services to customers. For the purpose of providing reliable and truthful service, a fair and elastic resource allocation strategy is essential from the standpoint of service customers. In this paper, we propose a game theoretic mechanism for dynamic cloud service management, including task assignment and resource allocation to provide reliable and truthful cloud services. A user utility function is first devised considering the dynamic characteristics of cloud computing. The elementary stepwise system is then applied to efficiently assign tasks to cloud servers. A resource allocation mechanism based on bargaining game solution is also adopted for fair resource allocation in terms of quality of service of requested tasks. Through numerical experiments, it is shown that the proposed mechanism guarantees better system performance than several existing methods. The experimental results show that the mechanism completes the requested tasks earlier with relatively higher utility while providing a significant level of fairness compared with existing ones. The proposed mechanism is expected to support cloud service providers in elastically managing their limited resources in a cloud computing environment in terms of quality of service. Copyright © 2013 John Wiley & Sons, Ltd.     

Multi-Issue Negotiation Processes by Evolutionary Simulation, Validation and Social Extensions

We describe a system for bilateral negotiations in which artificial agents aregenerated by an evolutionary algorithm (EA). The negotiations are governed bya finite-horizon version of the alternating-offers protocol. Several issuesare negotiated simulataneously. We first analyse and validate the outcomes ofthe evolutionary system, using the game-theoretic subgame-perfect equilibriumas a benchmark. We then present two extensions of the negotiation model. Inthe first extension agents take into account the fairness of the obtainedpayoff. We find that when the fairness norm is consistently applied during thenegotiation, agents reach symmetric outcomes which are robust and ratherinsensitive to the actual fairness settings. In the second extension we modela competitive market situation where agents have multiple bargainingopportunities before reaching the final agreement. Symmetric outcomes are nowalso obtained, even when the number of bargaining opportunities is small. Wefurthermore study the influence of search or negotiation costs in this game.     

Femtocell网络的鲁棒议价博弈功率控制

针对具有不完美信道状态信息的Femtocell双层网络，为了保证网络效用最大化、最小服务质量要求及Femtocell用户之间的效用公平，提出了基于议价博弈的鲁棒功率控制方案.在保证宏小区用户正常传输情况下，考虑到Femtocell家庭用户的最小服务质量要求，将Femtocell网络的鲁棒功率控制问题转化为议价博弈功率控制问题.为了保证Femtocell家庭用户之间的公平性，给出了Kalai-Smorodinsky（K-S）议价博弈解，证明了议价博弈解的存在性和唯一性，并提出了一种基于二分查找算法的分布式鲁棒功率控制方案.仿真结果表明，所提出的算法不仅具有较好的收敛性能，而且能够较好地保证用户之间的公平性.     

业务量工程中负载均衡与能量效率的折中——基于博弈论的多目标优化

本文研究了如何对业务量工程中的两个重要目标：负载均衡和能量效率进行公平折中。为此,本文基于纳什议价的框架,建立威胁值博弈模型来对业务量路由进行协商。为了避免博弈者自私决策而导致不公平的解或是议价失败,本文还将威胁值博弈拓展成重复博弈,并用机制设计来保证议价结果存在以及得到的解的公平性。通过严格的数学证明,以及在NSFNET中的应用可以看出,本文提出的方案不仅易于实施,还能保证对负载均衡和能量效率两个目标折中的公平性。     

基于RBS 的合作通信网络公平合作策略

针对合作通信网络中基于纳什议价解(NBS)的合作策略存在用户效用分配不公平的问题,同时考虑用户的最大与最小效用,提出了基于Raiffa-Kalai-Smorodinsk议价解(RBS)的合作策略,并建立了用户合作的条件.仿真结果表明,基于RBS的合作策略在保证网络总效用不变的前提下,具有更好的公平性.     

一种基于认知无线电系统的公平信道分配算法*

由于在认知无线电网络中主用户与认知用户共存,如何在不对主用户造成干扰的前提下.对认知用户进行合理的资源分配显得尤为重要.以纳什协调解为优化目标,并考虑功率约束,提出一种公平信道分配算法.在仿真中,对以吞吐量最大化为目标的Maximal-Rate策略和考虑公平的Max-Min策略进行了对比,仿真结果表明.本算法有着与Ma...     

Cooperative network design: A Nash bargaining solution approach

The Network Design problem has received increasing attention in recent years. Previous works have addressed this problem considering almost exclusively networks designed by selfish users, which can be consistently suboptimal. This paper addresses the network design issue using cooperative game theory, which permits to study ways to enforce and sustain cooperation among users. Both the Nash bargaining solution and the Shapley value are widely applicable concepts for solving these games. However, the Shapley value presents several drawbacks in this context.For this reason, we solve the cooperative network design game using the Nash bargaining solution (NBS) concept. More specifically, we extend the NBS approach to the case of multiple players and give an explicit expression for users’ cost allocations. We further provide a distributed algorithm for computing the Nash bargaining solution. Then, we compare the NBS to the Shapley value and the Nash equilibrium solution in several network scenarios, including real ISP topologies, showing its advantages and appealing properties in terms of cost allocation to users and computation time to obtain the solution.Numerical results demonstrate that the proposed Nash bargaining solution approach permits to allocate costs fairly to users in a reasonable computation time, thus representing a very effective framework for the design of efficient and stable networks.     

Joint spectrum allocation and scheduling for fair spectrum sharing in cognitive radio wireless networks

Cognitive radio and Dynamic Spectrum Access (DSA) enable wireless users to share a wide range of available spectrums. In this paper, we study joint spectrum allocation and scheduling problems in cognitive radio wireless networks with the objectives of achieving fair spectrum sharing. A novel Multi-Channel Contention Graph (MCCG) is proposed to characterize the impact of interference under the protocol model in such networks. Based on the MCCG, we present an optimal algorithm to compute maximum throughput solutions. As simply maximizing throughput may result in a severe bias on resource allocation, we take fairness into consideration by presenting optimal algorithms as well as fast heuristics to compute fair solutions based on a simplified max–min fairness model and the well-known proportional fairness model. Numerical results show that the performance given by our heuristic algorithms is very close to that of the optimal solution, and our proportional fair algorithms achieve a good tradeoff between throughput and fairness. In addition, we extend our research to the physical interference model, and propose effective heuristics for solving the corresponding problems.     

OFDMA无线mesh网中公平资源分配算法

为了兼顾用户间公平性的同时最大化总的端到端速率,并克服现有分配算法在实际中难以实现的缺点,提出了一种新的分级资源分配算法.该算法首先根据有限的信息基于纳什议价解(NBS)进行粗分配(CA);其次根据完整的子载波增益信息排序方法进行细分配(FA).仿真结果表明,该算法不仅获得与基于最大速率准则的算法相近的总的端到端速率,而且保证了用户间的公平性;同时,该算法能以更低的复杂度获得与现有算法相近的端到端速率.     

Multi-user symmetric cooperation based on nash bargaining solution in cooperative relay networks

This paper presents a symmetric cooperation strategy for cooperative relay networks with multiple users. The multi-user symmetric cooperation model and the relay selection algorithm are proposed. Then, the time slot allocation problem is cast into a bargaining problem, and the optimal time slot allocation solution is obtained by Nash bargaining solution (NBS). Moreover, we also consider the implementations of the cooperation strategy, i.e., the grouping and admission control algorithm. Simulation results show that users can obtain larger rates under the symmetric cooperation strategy than the non-cooperative case.     

A pricing strategy for job allocation in mobile grids using a non-cooperative bargaining theory framework

Due to their inherent limitations in computational and battery power, storage and available bandwidth, mobile devices have not yet been widely integrated into grid computing platforms. However, millions of laptops, PDAs and other portable devices remain unused most of the time, and this huge repository of resources can be potentially utilized, leading to what is called a mobile grid environment. In this paper, we propose a game theoretic pricing strategy for efficient job allocation in mobile grids. By drawing upon the Nash bargaining solution, we show how to derive a unified framework for addressing such issues as network efficiency, fairness, utility maximization, and pricing. In particular, we characterize a two-player, non-cooperative, alternating-offer bargaining game between the Wireless Access Point Server and the mobile devices to determine a fair pricing strategy which is then used to effectively allocate jobs to the mobile devices with a goal to maximize the revenue for the grid users. Simulation results show that the proposed job allocation strategy is comparable to other task allocation schemes in terms of the overall system response time.     

基于Stackerlberg和议价博弈的Femtocell网络功率控制

针对Femtocell网络中存在的干扰问题,提出一种基于Stackerlberg博弈和议价博弈的功率控制策略.首先,给出既可以使Femtocell网络系统容量最大化,又可以体现效用公平的效用函数;然后,在保证宏小区用户效用最大化的条件下,考虑到Femtocell家庭用户的收益,给出Stackelberg博弈模型;接着,考虑到Femtocell家庭用户之间的效用公平和最小服务质量要求,给出基于议价博弈的Kalai-Smorodinsky议价解,并证明议价解的存在性和唯一性.使用拉格朗日乘子法给出宏小区的最优价格,保证宏小区的效用最大化.仿真结果表明,该策略在满足宏蜂窝网络效用最大化的情况下,不但能够满足Femtocell家庭用户最小服务质量需求和公平性,而且Femtocell网络的收益也能得到较好的保证.     

Congestion control in utility fair networks

This paper deals with a congestion control framework for elastic and real-time traffic, where the user’s application is associated with a utility function. We allow users to have concave as well as non-concave utility functions, and aim at allocating bandwidth such that utility values are shared fairly. To achieve this, we transform all utilities into strictly concave second order utilities and interpret the resource allocation problem as the global optimization problem of maximizing aggregate second order utility. We propose a new fairness criterion, utility proportional fairness, which is characterized by the unique solution to this problem. Our fairness criterion incorporates utility max–min fairness as a limiting case. Based on our analysis, we obtain congestion control laws at links and sources that (i) are linearly stable regardless of the network topology, provided that a bound on round-trip-times is known, (ii) provide a utility proportional fair resource allocation in equilibrium. We further investigate the efficiency of utility fair resource allocations. Our measure of efficiency is defined as the worst case ratio of the total utility of a utility proportional fair rate vector and the maximum possible total utility. We present a generic technique, which allows to obtain upper bounds on the efficiency loss. For special cases, such as linear and concave utility functions, and non-concave utility functions with bounded domain, we explicitly calculate such upper bounds. Then, we study utility fair resource allocations with respect to bandwidth fairness. We derive a fairness metric assessing the aggressiveness of utility functions. This allows us to design fair utility functions for various applications. Finally, we simulate the proposed algorithms using the NS2 simulator.     

Fairness of medium access control protocols for multi-hop ad hoc wireless networks

It is an undisputed fact that fairness is an important element of a well-designed medium access control (MAC) protocol for multi-hop ad hoc networks. However, most popular MAC protocols still fail to attain an acceptable level of fairness in media access although several enhancements have been proposed in the past. These proposed enhancements are effective only in limited scenarios. It is our objective in this paper to do the following: (i) analyze the fairness problem; (ii) identify and analyze the three main causes leading to the fairness problem, namely, the lack of synchronization problem (LSP), the double contention areas problem (DCP) and the lack of coordination problem (LCP); (iii) based on the analysis, propose a new MAC protocol named the extended hybrid asynchronous time division multiple access (EHATDMA) as a solution. For better assessment of fairness, we have designed an index named max–min fairness index, which is scenario-independent and reflects the difference between the fair sharing provided by a protocol and the ideal max–min fair sharing. Comprehensive simulations have been carried out to compare the fairness of our protocol with the existing ones. Simulation results show that although the existing protocols employ various enhancements meant to improve the fairness property, most of them are still strongly biased towards throughput when a conflict between throughput and fairness arises. In addition, the fairness performance of these protocols varies widely from one scenario to another. On the other hand, EHATDMA strikes a good balance between throughput and fairness. It delivers a consistently high level of fairness regardless of network topology, traffic load and radio parameters, yet maintains high throughput whenever possible. Our simulation results also reveal that the most important mechanism affecting the fair sharing of radio channels among flows is the non-work-conserving mechanism.     

基于议价机制的网格资源交易算法

资源管理是网格技术研究的核心任务之一。针对网格资源异构性、动态性、自治性等特点提出了基于议价机制的网格资源交易算法。分析了网格资源管理的市场模型,指出市场模型中各角色的特点,提出了网格资源管理的议价模型。针对这种模型,提出了基于议价时限和价格变化率的网格资源交易算法,并根据平衡策略给出了该算法的描述。