Applications of Repeated Games in Wireless Networks: A Survey

A repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model an interaction among players in only one period, in repeated games, interactions of players repeat for multiple periods; and thus the players become aware of other players' past behaviors and their future benefits, and will adapt their behavior accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey the applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games to encourage wireless nodes to cooperate, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference

Survey on Multi Agent Energy Efficient Clustering Algorithms in Wireless Sensor Networks

In the last few years, there are many applications for Wireless Sensor Networks (WSNs). One of the main drawbacks of these networks is the limited battery power of sensor nodes. There are many cases to reduce energy consumption in WSNs. One of them is clustering. Sensor nodes partitioned into the clusters so that one is chosen as Cluster Head (CH). Clustering and selection of the proper node as CH is very significant in reducing energy consumption and increasing network lifetime. In this paper, we have surveyed a multi agent clustering algorithms and compared on various parameters like cluster size, cluster count, clusters equality, parameters used in CHs selection, algorithm complexity, types of algorithm used in clustering, nodes location awareness, inter-cluster and intra-cluster topologies, nodes homogeneity and MAC layer communications

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

A Survey on Energy-Efficient Strategies in Static Wireless Sensor Networks

A comprehensive analysis on the energy-efficient strategy in static Wireless Sensor Networks (WSNs) that are not equipped with any energy harvesting modules is conducted in this article. First, a novel generic mathematical definition of Energy Efficiency (EE) is proposed, which takes the acquisition rate of valid data, the total energy consumption, and the network lifetime of WSNs into consideration simultaneously. To the best of our knowledge, this is the first time that the EE of WSNs is mathematically defined. The energy consumption characteristics of each individual sensor node and the whole network are expounded at length. Accordingly, the concepts concerning EE, namely the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective, are proposed. Subsequently, the relevant energy-efficient strategies proposed from 2002 to 2019 are tracked and reviewed. Specifically, they respectively are classified into five categories: the Energy-Efficient Media Access Control protocol, the Mobile Node Assistance Scheme, the Energy-Efficient Clustering Scheme, the Energy-Efficient Routing Scheme, and the Compressive Sensing--based Scheme. A detailed elaboration on both of the basic principle and the evolution of them is made. Finally, further analysis on the categories is made and the related conclusion is drawn. To be specific, the interdependence among them, the relationships between each of them, and the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective are analyzed in detail. In addition, the specific applicable scenarios for each of them and the relevant statistical analysis are detailed. The proportion and the number of citations for each category are illustrated by the statistical chart. In addition, the existing opportunities and challenges facing WSNs in the context of the new computing paradigm and the feasible direction concerning EE in the future are pointed out

Energy Efficient and Secure Wireless Sensor Networks Design

Wireless Sensor Networks (WSNs) are emerging technologies that have the ability to sense, process, communicate, and transmit information to a destination, and they are expected to have significant impact on the efficiency of many applications in various fields. The resource constraint such as limited battery power, is the greatest challenge in WSNs design as it affects the lifetime and performance of the network. An energy efficient, secure, and trustworthy system is vital when a WSN involves highly sensitive information. Thus, it is critical to design mechanisms that are energy efficient and secure while at the same time maintaining the desired level of quality of service. Inspired by these challenges, this dissertation is dedicated to exploiting optimization and game theoretic approaches/solutions to handle several important issues in WSN communication, including energy efficiency, latency, congestion, dynamic traffic load, and security. We present several novel mechanisms to improve the security and energy efficiency of WSNs. Two new schemes are proposed for the network layer stack to achieve the following: (a) to enhance energy efficiency through optimized sleep intervals, that also considers the underlying dynamic traffic load and (b) to develop the routing protocol in order to handle wasted energy, congestion, and clustering. We also propose efficient routing and energy-efficient clustering algorithms based on optimization and game theory. Furthermore, we propose a dynamic game theoretic framework (i.e., hyper defense) to analyze the interactions between attacker and defender as a non-cooperative security game that considers the resource limitation. All the proposed schemes are validated by extensive experimental analyses, obtained by running simulations depicting various situations in WSNs in order to represent real-world scenarios as realistically as possible. The results show that the proposed schemes achieve high performance in different terms, such as network lifetime, compared with the state-of-the-art schemes