Game theory for dynamic spectrum sharing cognitive radio

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University on 21 June 2010.‘Game Theory’ is the formal study of conflict and cooperation. The theory is based on a set of tools that have been developed in order to assist with the modelling and analysis of individual, independent decision makers. These actions potentially affect any decisions, which are made by other competitors. Therefore, it is well suited and capable of addressing the various issues linked to wireless communications. This work presents a Green Game-Based Hybrid Vertical Handover Model. The model is used for heterogeneous wireless networks, which combines both dynamic (Received Signal Strength and Node Mobility) and static (Cost, Power Consumption and Bandwidth) factors. These factors control the handover decision process; whereby the mechanism successfully eliminates any unnecessary handovers, reduces delay and overall number of handovers to 50% less and 70% less dropped packets and saves 50% more energy in comparison to other mechanisms. A novel Game-Based Multi-Interface Fast-Handover MIPv6 protocol is introduced in this thesis as an extension to the Multi-Interface Fast-handover MIPv6 protocol. The protocol works when the mobile node has more than one wireless interface. The protocol controls the handover decision process by deciding whether a handover is necessary and helps the node to choose the right access point at the right time. In addition, the protocol switches the mobile nodes interfaces ‘ON’ and ‘OFF’ when needed to control the mobile node’s energy consumption and eliminate power lost of adding another interface. The protocol successfully reduces the number of handovers to 70%, 90% less dropped packets, 40% more received packets and acknowledgments and 85% less end-to-end delay in comparison to other Protocols. Furthermore, the thesis adapts a novel combination of both game and auction theory in dynamic resource allocation and price-power-based routing in wireless Ad-Hoc networks. Under auction schemes, destinations nodes bid the information data to access to the data stored in the server node. The server will allocate the data to the winner who values it most. Once the data has been allocated to the winner, another mechanism for dynamic routing is adopted. The routing mechanism is based on the source-destination cooperation, power consumption and source-compensation to the intermediate nodes. The mechanism dramatically increases the seller’s revenue to 50% more when compared to random allocation scheme and briefly evaluates the reliability of predefined route with respect to data prices, source and destination cooperation for different network settings. Last but not least, this thesis adjusts an adaptive competitive second-price pay-to-bid sealed auction game and a reputation-based game. This solves the fairness problems associated with spectrum sharing amongst one primary user and a large number of secondary users in a cognitive radio environment. The proposed games create a competition between the bidders and offers better revenue to the players in terms of fairness to more than 60% in certain scenarios. The proposed game could reach the maximum total profit for both primary and secondary users with better fairness; this is illustrated through numerical results

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

A Hierarchical Spectrum Access Scheme for TV White Space Coexistence in Hetergeneous Networks

Among current techniques for dynamic access to television (TV) white space (TVWS), geolocation database-based access provides a promising performance in protecting the TV-band incumbents from interference that cannot be efficiently achieved in other license-exempt models. However, in heterogeneous wireless networks, most portable devices do not have such access and may cause interference to TV incumbents. We propose a hierarchical model for spectrum sharing in TVWS that includes a wide range of fixed and portable devices. In the first tier, the TV broadcaster can lease the spectrum bands to local fixed users based on a soft license agreement. The fixed users are allowed to share access to this spectrum with some mobile users in their proximity in exchange for cooperative relaying. We consider a practical scenario, where only partial channel state information (CSI) is available at the users\u27 transmitters, and we propose a robust algorithm against such uncertainties in CSI values. We also propose a reputation-based relay selection mechanism to identify selfish portable users. The proposed spectrum sharing framework can provide a practical model for TVWS-coexistence that prevents undesired interference to the incumbents while restricting interference among the unlicensed devices. The simulation results show the enhancement of fixed users\u27 rate compared with alternative relay selection methods

Byzantine Attack and Defense in Cognitive Radio Networks: A Survey

The Byzantine attack in cooperative spectrum sensing (CSS), also known as the spectrum sensing data falsification (SSDF) attack in the literature, is one of the key adversaries to the success of cognitive radio networks (CRNs). In the past couple of years, the research on the Byzantine attack and defense strategies has gained worldwide increasing attention. In this paper, we provide a comprehensive survey and tutorial on the recent advances in the Byzantine attack and defense for CSS in CRNs. Specifically, we first briefly present the preliminaries of CSS for general readers, including signal detection techniques, hypothesis testing, and data fusion. Second, we analyze the spear and shield relation between Byzantine attack and defense from three aspects: the vulnerability of CSS to attack, the obstacles in CSS to defense, and the games between attack and defense. Then, we propose a taxonomy of the existing Byzantine attack behaviors and elaborate on the corresponding attack parameters, which determine where, who, how, and when to launch attacks. Next, from the perspectives of homogeneous or heterogeneous scenarios, we classify the existing defense algorithms, and provide an in-depth tutorial on the state-of-the-art Byzantine defense schemes, commonly known as robust or secure CSS in the literature. Furthermore, we highlight the unsolved research challenges and depict the future research directions.Comment: Accepted by IEEE Communications Surveys and Tutoiral

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