基于多智能体强化学习的区块链赋能车联网中的安全数据共享

针对基于委托权益证明(Delegated Proof-of-Stake, DPoS) 共识算法的区块链赋能车联网系统中区块验证的安全性与可靠性问题, 矿工通过引入轻节点(如智能手机等边缘节点)共同参与区块验证,提高区块验证的安全性和可靠性。为了激励矿工主动引入轻节点, 采用了斯坦伯格(Stackelberg)博弈模型对区块链用户与矿工进行建模, 实现区块链用户的效用和矿工的个人利润最大化。作为博弈主方的区块链用户设定最优的区块验证的交易费, 而作为博弈从方的矿工决定最优的招募验证者(即轻节点)的数量。为了找到所设计Stackelberg博弈的纳什均衡, 设计了一种基于多智能体强化学习算法来搜索接近最优的策略。最后对本文方案进行验证, 结果表明该方案既能实现区块链用户和矿工效益最大化, 也能保证区块验证的安全性与可靠性。     

智能无线通信技术研究概况

近年来,人工智能技术已被应用于无线通信领域,以解决传统无线通信技术面对信息爆炸和万物互联等新发展趋势所遇到的瓶颈问题.首先介绍深度学习、深度强化学习和联邦学习三类具有代表性的人工智能技术;然后通过对这三类技术在无线通信中的无线传输、频谱管理、资源配置、网络接入、网络及系统优化5个方面的应用进行综述,分析和总结它们在解决...     

On Measuring Disturbances in the Force: Advanced Cloud Monitoring Systems

Monitoring large scale infrastructures hosting an even larger number of applications in highly consolidated multi-tenant environments presents a wealth of problems. Dealing with these challenges is essential since monitoring is the cornerstone to make clouds responsive, failure-tolerant, automated and cost-efficient for operators. In this special issue, you will find the foundations together with cutting-edge developments in the state of the art of cloud monitoring systems. This special issue is targeted at a broad readership, ranging from newcomers wanting a smooth acquaintance with these technologies and experts aiming to dive deeper into the latest developments.     

Competitive Pricing for Spectrum Sharing in Cognitive Radio Networks: Dynamic Game, Inefficiency of Nash Equilibrium, and Collusion

We address the problem of spectrum pricing in a cognitive radio network where multiple primary service providers compete with each other to offer spectrum access opportunities to the secondary users. By using an equilibrium pricing scheme, each of the primary service providers aims to maximize its profit under quality of service (QoS) constraint for primary users. We formulate this situation as an oligopoly market consisting of a few firms and a consumer. The QoS degradation of the primary services is considered as the cost in offering spectrum access to the secondary users. For the secondary users, we adopt a utility function to obtain the demand function. With a Bertrand game model, we analyze the impacts of several system parameters such as spectrum substitutability and channel quality on the Nash equilibrium (i.e., equilibrium pricing adopted by the primary services). We present distributed algorithms to obtain the solution for this dynamic game. The stability of the proposed dynamic game algorithms in terms of convergence to the Nash equilibrium is studied. However, the Nash equilibrium is not efficient in the sense that the total profit of the primary service providers is not maximized. An optimal solution to gain the highest total profit can be obtained. A collusion can be established among the primary services so that they gain higher profit than that for the Nash equilibrium. However, since one or more of the primary service providers may deviate from the optimal solution, a punishment mechanism may be applied to the deviating primary service provider. A repeated game among primary service providers is formulated to show that the collusion can be maintained if all of the primary service providers are aware of this punishment mechanism, and therefore, properly weight their profits to be obtained in the future.     

IEEE 802.16/WiMAX-based broadband wireless access and its application for telemedicine/e-health services

In this article we investigate the application of IEEE 802.16-based broadband wireless access (BWA) technology to telemedicine services and the related protocol engineering issues. An overview of the different evolutions of the IEEE 802.16 standard is presented and some open research issues are identified. A survey on radio resource management, traffic scheduling, and admission control mechanisms proposed for IEEE 802.16/WiMAX systems is also provided. A qualitative comparison between third-generation wireless systems and the IEEE 802.16/WiMAX technology is given. A survey on telemedicine services using traditional wireless systems is presented. The advantages of using IEEE 802.16/WiMAX technology over traditional wireless systems, as well as the related design issues and approaches are discussed. To this end, we present a bandwidth allocation and admission control algorithm for IEEE 802.16-based BWA designed specifically for wireless telemedicine/e-health services. This algorithm aims at maximizing the utilization of the radio resources while considering the quality of service requirements for telemedicine traffic. Some performance evaluation results for this scheme are obtained by simulations     

Sleep and Wakeup Strategies in Solar-Powered Wireless Sensor/Mesh Networks: Performance Analysis and Optimization

A queuing analytical model is presented to investigate the performances of different sleep and wakeup strategies in a solar-powered wireless sensor/mesh network where a solar cell is used to charge the battery in a sensor/mesh node. While the solar radiation process (and, hence, the energy generation process in a solar cell) is modeled by a stochastic process (i.e., a Markov chain), a linear battery model with relaxation effect is used to model the battery capacity recovery process. Developed based on a multidimensional discrete-time Markov chain, the presented model is used to analyze the performances of different sleep and wakeup strategies in a sensor/mesh node. The packet dropping and packet blocking probabilities at a node are the major performance metrics. The numerical results obtained from the analytical model are validated by extensive simulations. In addition, using the queuing model, based on a game-theoretic formulation, we demonstrate how to obtain the optimal parameters for a particular sleep and wakeup strategy. In this case, we formulate a bargaining game by exploiting the trade-off between packet blocking and packet dropping probabilities due to the sleep and wakeup dynamics in a sensor/mesh node. The Nash solution is obtained for the equilibrium point of sleep and wakeup probabilities. The presented queuing model, along with the game-theoretic formulation, would be useful for the design and optimization of energy-efficient protocols for solar-powered wireless sensor/mesh networks under quality-of-service (QoS) constraints     

Adaptive Fair Subcarrier/Rate Allocation in Multirate OFDMA Networks: Radio Link Level Queuing Performance Analysis

This paper presents a semi-analytical methodology for radio link level performance analysis in a multirate "orthogonal frequency-division multiple-access" (OFDMA) network with adaptive fair rate allocation. Multirate transmission is assumed to be achieved through adaptive modulation, and fair rate allocation is based on the principle of generalized processor sharing to allocate the subcarriers adaptively among the users. The fair rate allocation problem is formulated as an optimization problem with the objective of maximizing system throughput while maintaining fairness (in terms of transmission rate) among the users. The "optimal" fair rate allocation is obtained by using the "Hungarian method." A heuristic-based approach, namely the "iterative approach," that is more implementation friendly is also presented. The throughput performance of the iterative fair rate allocation is observed to be as good as that of optimal fair rate allocation and is better than that of the static subcarrier allocation scheme. Also, the iterative fair allocation provides better fairness compared to that for each of the optimal and the static subcarrier allocation schemes. To this end, a queuing model is formulated to analyze radio link level performance measures such as packet dropping probability and packet transmission delay under the above rate allocation schemes. In this formulation, packet arrivals are modeled by the discrete Markov modulated Poisson process, which is flexible to model different types of traffic arrival patterns. The proposed framework for radio link level performance analysis of multirate OFDMA networks is validated by extensive simulations. Also, examples on the application of the proposed model for connection admission control and quality-of-service provisioning are illustrated     

Call-Level and Packet-Level Quality of Service and User Utility in Rate-Adaptive Cellular CDMA Networks: A Queuing Analysis

A queuing analytical model is presented to evaluate call-level and packet-level quality of service (QoS) metrics in the uplink of a voice/data cellular code division multiple access (CDMA) network. In this model, a threshold-based call admission control (CAC) is used to limit the number of admitted calls in a cell and also to prioritize handoff calls over new calls. The transmission rates for data calls can be adjusted to accommodate more voice and/or data calls while satisfying the minimum signal-to-interference ratio (SIR)/ transmission rate requirement. Also, automatic repeat request (ARQ)-based error control is used for improved reliability of data packets. Call-level performance measures for both voice and data calls and packet-level performance measures specifically for data calls can be obtained from the analytical model. The interdependencies among call-level and packet-level QoS metrics are investigated under different CAC, rate adaptation, and error control parameter settings. To this end, the level of users' satisfaction (or user utility) is formulated as a function of the QoS metrics and an optimization formulation is presented to obtain the local-optimal system parameters