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

Game theory for collaboration in future networks

Cooperative strategies have the great potential of improving network performance and spectrum utilization in future networking environments. This new paradigm in terms of network management, however, requires a novel design and analysis framework targeting a highly flexible networking solution with a distributed architecture. Game Theory is very suitable for this task, since it is a comprehensive mathematical tool for modeling the highly complex interactions among distributed and intelligent decision makers. In this way, the more convenient management policies for the diverse players (e.g. content providers, cloud providers, home providers, brokers, network providers or users) should be found to optimize the performance of the overall network infrastructure. The authors discuss in this chapter several Game Theory models/concepts that are highly relevant for enabling collaboration among the diverse players, using different ways to incentivize it, namely through pricing or reputation. In addition, the authors highlight several related open problems, such as the lack of proper models for dynamic and incomplete information games in this area.info:eu-repo/semantics/acceptedVersio

Game theory for cooperation in multi-access edge computing

Cooperative strategies amongst network players can improve network performance and spectrum utilization in future networking environments. Game Theory is very suitable for these emerging scenarios, since it models high-complex interactions among distributed decision makers. It also finds the more convenient management policies for the diverse players (e.g., content providers, cloud providers, edge providers, brokers, network providers, or users). These management policies optimize the performance of the overall network infrastructure with a fair utilization of their resources. This chapter discusses relevant theoretical models that enable cooperation amongst the players in distinct ways through, namely, pricing or reputation. In addition, the authors highlight open problems, such as the lack of proper models for dynamic and incomplete information scenarios. These upcoming scenarios are associated to computing and storage at the network edge, as well as, the deployment of large-scale IoT systems. The chapter finalizes by discussing a business model for future networks.info:eu-repo/semantics/acceptedVersio

Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions.

Exploring and monitoring the underwater world using underwater sensors is drawing a lot of attention these days. In this field cooperation between acoustic sensor nodes has been a critical problem due to the challenging features such as acoustic channel failure (sound signal), long propagation delay of acoustic signal, limited bandwidth and loss of connectivity. There are several proposed methods to improve cooperation between the nodes by incorporating information/game theory in the node's cooperation. However, there is a need to classify the existing works and demonstrate their performance in addressing the cooperation issue. In this paper, we have conducted a review to investigate various factors affecting cooperation in underwater acoustic sensor networks. We study various cooperation techniques used for underwater acoustic sensor networks from different perspectives, with a concentration on communication reliability, energy consumption, and security and present a taxonomy for underwater cooperation. Moreover, we further review how the game theory can be applied to make the nodes cooperate with each other. We further analyze different cooperative game methods, where their performance on different metrics is compared. Finally, open issues and future research direction in underwater acoustic sensor networks are highlighted

Multi Attacker Collision Analysis In MANETs Using Conditional likilihood

Mobile ad hoc networks will aim to provide services to the wireless network without depending on any fixed infrastructure There are basically two approaches to motivate players: 1) by denying service to misbehaving players by means of a reputation mechanism or 2) by remunerating honest players, using for example a micropayment scheme. In these works, malicious players are modelled as never cooperative, without any further sophistication, since their main focus was discouraging selfish players. There is no degree of selfishness that can approximate the behaviour of malicious players. This work will focus on multi-attacker collusion in the regular/malicious player game. The Proposed System also model the regular/malicious player game as a multistage dynamic Bayesian signalling game to find the optimal strategy of regular and malicious players. Apart from that utility function, degree of selfishness of a player and degree of uncertainty are also considered

A Multi-Objective Routing Algorithm Based on Auction Game for Space Information Network

This paper aims to create a resource-saving method for the routing problem in space information network. To this end, a multi-objective routing algorithm was created based on game theory for space information network. Specifically, the auction game was introduced to solve the routing problem using the delay-tolerating network (DTN) protocol. Considering the topological periodicity of low earth orbit (LEO) satellite network, a typical space information network, the dynamic topological structure was divided into relatively static time slots. Then, the routing problem was solved through the auction game in these slots. The proposed algorithm can minimize the number of selfish nodes in the network and avoid network congestion resulted from excessive resource consumption of individual nodes. Finally, the proposed algorithm was compared with other well-known routing models like the epidemic routing model (Epidemic) and the first contact routing model (FC). The results show that the proposed algorithm outperformed the contrastive models in both average delay and network overhead ratio. The research findings shed important new light on the routing of space information network

Game Theory for Multi-Access Edge Computing:Survey, Use Cases, and Future Trends

Game theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming multiaccess edge computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as quality of experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely, rational versus evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse tradeoffs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios

Socio-economic aware data forwarding in mobile sensing networks and systems

The vision for smart sustainable cities is one whereby urban sensing is core to optimising city operation which in turn improves citizen contentment. Wireless Sensor Networks are envisioned to become pervasive form of data collection and analysis for smart cities but deployment of millions of inter-connected sensors in a city can be cost-prohibitive. Given the ubiquity and ever-increasing capabilities of sensor-rich mobile devices, Wireless Sensor Networks with Mobile Phones (WSN-MP) provide a highly flexible and ready-made wireless infrastructure for future smart cities. In a WSN-MP, mobile phones not only generate the sensing data but also relay the data using cellular communication or short range opportunistic communication. The largest challenge here is the efficient transmission of potentially huge volumes of sensor data over sometimes meagre or faulty communications networks in a cost-effective way. This thesis investigates distributed data forwarding schemes in three types of WSN-MP: WSN with mobile sinks (WSN-MS), WSN with mobile relays (WSN-HR) and Mobile Phone Sensing Systems (MPSS). For these dynamic WSN-MP, realistic models are established and distributed algorithms are developed for efficient network performance including data routing and forwarding, sensing rate control and and pricing. This thesis also considered realistic urban sensing issues such as economic incentivisation and demonstrates how social network and mobility awareness improves data transmission. Through simulations and real testbed experiments, it is shown that proposed algorithms perform better than state-of-the-art schemes.Open Acces

Design and optimisation of a low cost Cognitive Mesh Network

Wireless Mesh Networks (WMNs) have been touted as the most promising wireless technology in providing high-bandwidth Internet access to rural, remote and under-served areas, with relatively lower investment cost as compared to traditional access networks. WMNs structurally comprise of mesh routers and mesh clients. Furthermore, WMNs have an envisaged ability to provide a heterogeneous network system that integrates wireless technologies such as IEEE 802.22 WRAN, IEEE 802.16 WiMAX, IEEE 802.11 Wi-Fi, Blue-tooth etc. The recent proliferation of new devices on the market such as smart phones and, tablets, and the growing number of resource hungry applications has placed a serious strain on spectrum availability which gives rise to the spectrum scarcity problem. The spectrum scarcity problem essentially results in increased spectrum prices that hamper the growth and efficient performance of WMNs as well as subsequent transformation of WMN into the envisaged next generation networks. Recent developments in TV white space communications technology and the emergence of Cognitive radio devices that facilitate Dynamic Spectrum Access (DSA) have provided an opportunity to mitigate the spectrum scarcity problem. To solve the scarcity problem, this thesis reconsiders the classical Network Engineering (NE) and Traffic Engineering (TE) problems to objectively design a low cost Cognitive Mesh network that promotes efficient resources utilization and thereby achieve better Quality of Service (QoS) levels