A Novel Analytical Framework for Integrated Cross-Layer Study of Call-Level and Packet-Level QoS in Wireless Mobile Multimedia Networks

We present a novel integrated analytical framework for analyzing the quality-of-service (QoS) performance measures in a wireless mobile multimedia network. The framework integrates physical, radio link, and network layer parameters and protocols to analyze the call-level and packet-level performances. In the network layer, call admission control (CAC) is responsible for deciding whether an incoming call can be accepted or not so that the performances of the ongoing calls do not deteriorate below the acceptable level. Also, an adaptive channel allocation (ACA) scheme is used to maximize the utilization of the radio resources. In the data link layer, queue management and error control are used for non-real-time loss-sensitive traffic. In the physical layer, a finite state Markov channel (FSMC) is used to model channel fading, and adaptive modulation is used for rate adaptation according to channel quality. Various call-level and packet-level QoS measures for real-time, non-real-time, and best-effort traffic are obtained. The analytical results are validated by extensive simulations. Examples of the applications of the presented analytical framework are also provided     

Cognitive radio for next-generation wireless networks: an approach to opportunistic channel selection in ieee 802.11-based wireless mesh - [accepted from open call]

?Cognitive radio? has emerged as a new design paradigm for next-generation wireless networks that aims to increase utilization of the scarce radio spectrum (both licensed and unlicensed). Learning and adaptation are two significant features of a cognitive radio transceiver. Intelligent algorithms are used to learn the surrounding environment, and the knowledge thus obtained is utilized by the transceiver to choose the frequency band (i.e., channel) of transmission as well as transmission parameters to achieve the best performance. In this article we first provide an overview of the different components to achieve adaptability in a cognitive radio transceiver and discuss the related approaches. A survey of the cognitive radio techniques used in the different wireless systems is then presented. To this end, a dynamic opportunistic channel selection scheme based on the cognitive radio concept is presented for an IEEE 802.11-based wireless mesh network.     

Dynamics of Multiple-Seller and Multiple-Buyer Spectrum Trading in Cognitive Radio Networks: A Game-Theoretic Modeling Approach

We consider the problem of spectrum trading with multiple licensed users (i.e., primary users) selling spectrum opportunities to multiple unlicensed users (i.e., secondary users). The secondary users can adapt the spectrum buying behavior (i.e., evolve) by observing the variations in price and quality of spectrum offered by the different primary users or primary service providers. The primary users or primary service providers can adjust their behavior in selling the spectrum opportunities to secondary users to achieve the highest utility. In this paper, we model the evolution and the dynamic behavior of secondary users using the theory of evolutionary game. An algorithm for the implementation of the evolution process of a secondary user is also presented. To model the competition among the primary users, a noncooperative game is formulated where the Nash equilibrium is considered as the solution (in terms of size of offered spectrum to the secondary users and spectrum price). For a primary user, an iterative algorithm for strategy adaptation to achieve the solution is presented. The proposed game-theoretic framework for modeling the interactions among multiple primary users (or service providers) and multiple secondary users is used to investigate network dynamics under different system parameter settings and under system perturbation.     

A hierarchical framework of dynamic relay selection for mobile users and profit maximization for service providers in wireless relay networks

Although extensive research has been carried out on the issue of how to optimally select relays in wireless relay networks, relay selection for mobile users is still a challenging problem because of the requirement that the dynamic selection should adapt to user mobility. Moreover, because the selected relays consume their energy on relaying data for the users, it is required that the users have to pay for this relay service. The price of selecting relays will affect the users' decisions. Assuming that different relays can belong to different service providers, we consider the situation that the service providers can strategically set the prices of their relays to maximize their profits. In this paper, we jointly study the dynamic relay selection for mobile users and profit maximization for service providers. Also, we design a Stackelberg‐game hierarchical framework to obtain the solution. At the lower level, we investigate the relay selection problem for the mobile users under given prices of selecting the relays. It is formulated as a Markov decision process problem with the objective to minimize the mobile user's long‐term average cost (which consists of the payment to the relay service and the cost due to packet loss), and solved by applying the linear programming technique. At the upper level, we study the game of setting relay prices for the service providers, with the knowledge that the mobile users will make relay selections based on their given prices. Nash equilibrium is obtained as the solution. Our results can help to provide a guidance for service providers to compete for providing relay services. Copyright © 2012 John Wiley & Sons, Ltd.     

A survey of mobile cloud computing: architecture,applications, and approaches

Together with an explosive growth of the mobile applications and emerging of cloud computing concept, mobile cloud computing (MCC) has been introduced to be a potential technology for mobile services. MCC integrates the cloud computing into the mobile environment and overcomes obstacles related to the performance (e.g., battery life, storage, and bandwidth), environment (e.g., heterogeneity, scalability, and availability), and security (e.g., reliability and privacy) discussed in mobile computing. This paper gives a survey of MCC, which helps general readers have an overview of the MCC including the definition, architecture, and applications. The issues, existing solutions, and approaches are presented. In addition, the future research directions of MCC are discussed. Copyright © 2011 John Wiley & Sons, Ltd.     

Overview on intelligent wireless communication technology

In recent years,artificial intelligence (AI) has been applied to wireless communications,in order to address the challenges introduced by data explosion and Internet of everything.Firstly,three core technologies of AI were introduced,including deep learning,deep reinforcement learning,and federated learning.Then,an overview of their applications on wireless communications was provided,from the aspects of wireless transmission,spectrum management,resource allocation,network access,network and system optimization.Based on the overview,the principle,applicability,design methodology,pros and cons on applying AI technologies to solve wireless communication problems were analyzed and summarized.Regarding the existed limitations,the future development trends and research directions on intelligent wireless communication technologies were pointed out,to hopefully provide useful help and reference for the future research in this field.     

Call admission control for QoS provisioning in 4G wireless networks: issues and approaches

This article presents a survey on the issues and the approaches related to designing call admission control schemes for fourth-generation wireless systems. We review the state of the art of CAC algorithms used in the traditional wireless networks. The major challenges in designing the CAC schemes for 4G wireless networks are identified. These challenges are mainly due to heterogeneous wireless access environments, provisioning of quality of service to multiple types of applications with different requirements, provisioning for adaptive bandwidth allocation, consideration of both call-level and packet-level performance measures, and consideration of QoS at both the air interface and the wired Internet. To this end, architecture of a two-tier CAC scheme for a differentiated services cellular wireless network is presented. The proposed CAC architecture is based on the call-level and packet-level QoS considerations at both the wireless and wired parts of the network. A performance analysis model for an example CAC scheme based on this architecture is outlined, and typical numerical results are presented.     

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。     

Deferrable load scheduling under imperfect data communication channel

In smart grid, the real‐time pricing is implemented to motivate power consumers to change their consumption profile dynamically. With the real‐time pricing, a deferrable load can be scheduled by its scheduler optimally so that the power consumption cost will be minimized. However, when the data communication in smart grid suffers from interference, congestion, malfunction in devices, or even cyber attack, it is possible that the power price information cannot be transmitted successfully to the scheduler. As a result, the scheduling performance will be negatively affected by the suboptimal decision‐making because of incomplete power price information. To overcome this problem, a partially observable Markov decision process based deferrable load scheduling algorithm is proposed. Besides, the implementation of a standby alternative channel with the purpose to improve the reliability of the data communication in smart grid is also discussed in this paper. The numerical results show that the proposed partially observable Markov decision process based algorithm and the implementation of standby channel can effectively improve the scheduling performance when the scheduler lacks actual price information. Copyright © 2014 John Wiley & Sons, Ltd.     

Offloading in Software Defined Network at Edge with Information Asymmetry: A Contract Theoretical Approach

The proliferation of highly capable mobile devices such as smartphones and tablets has significantly increased the demand for wireless access. Software defined network (SDN) at edge is viewed as one promising technology to simplify the traffic offloading process for current wireless networks. In this paper, we investigate the incentive problem in SDN-at-edge of how to motivate a third party access points (APs) such as WiFi and smallcells to offload traffic for the central base stations (BSs). The APs will only admit the traffic from the BS under the precondition that their own traffic demand is satisfied. Under the information asymmetry that the APs know more about own traffic demands, the BS needs to distribute the payment in accordance with the APs’ idle capacity to maintain a compatible incentive. First, we apply a contract-theoretic approach to model and analyze the service trading between the BS and APs. Furthermore, other two incentive mechanisms: optimal discrimination contract and linear pricing contract are introduced to serve as the comparisons of the anti adverse selection contract. Finally, the simulation results show that the contract can effectively incentivize APs’ participation and offload the cellular network traffic. Furthermore, the anti adverse selection contract achieves the optimal outcome under the information asymmetry scenario.