Game-Based Control Approach for Smart Grid

The concept of smart grid to transform the old power grid into a smart and intelligent electric power distribution system is, currently, a hot research topic. Smart grid offers the merging of electrical power engineering technologies with network communications. Game theory has featured as an interesting technique, adopted by many researchers, to establish effective smart grid communications. The use of game theory has offered solutions to various decision-making problems, ranging from distributed load management to micro storage management in smart grid. Interestingly, different researchers have different objectives or problem scopes for adopting game theory in smart grid. This chapter explores the game-based approach.

Bargaining Solutions for Resource Allocation Problems

The first unified and systematic treatment of the modern theory of bargaining is presented together with many examples of how that theory is applied in a variety of bargaining situations. This chapter provides a masterful synthesis of the fundamental results and insights obtained from the wide-ranging and diverse bargaining theory literature. Furthermore, it develops new analyses and results, especially on the relative impacts of two or more forces on the bargaining outcome. Many topics—such as inside options, commitment tactics, and repeated bargaining situations—receive their most extensive treatment to date.

Power Control Schemes Based on Game Theory

Power control is the intelligent selection of transmitter power output in a communication system to achieve good performance within the system. The notion of good performance can depend on context and may include optimizing metrics such as link data rate, network capacity, geographic coverage and range, and life of the network and network devices. Power control algorithms are used in many contexts, including cellular networks, sensor networks, and wireless LANs. Typically, there is no simple answer to the problem of power control, and a good algorithm must strike a balance between the benefits and drawbacks associated with targeting a particular transmit power based on the performance criteria of most importance to the designer. This chapter discusses power control schemes.

Game Models in Various Applications

Recently, game-theoretic models have become famous in many academic research areas. Therefore, many applications and extensions of the original game theoretic approach appear in many of the major science fields. Despite all the technical problems, the history of game theory suggests that it would be premature to abandon the tool, especially in the absence of a viable alternative. If anything, the development of game theory has been driven precisely by the realization of its limitations and attempts to overcome them. This chapter explores these ideas.

Introduction

The situations to which game theory has actually been applied reflect its selective usefulness for problems and solutions of an individualistic and competitive nature, building in the values of the status quo. The main principal area of application has been economics. In economics, game theory has been used in studying competition for markets, advertising, planning under uncertainty, and so forth. Recently, game theory has also been applied to many other fields, such as law, ethics, sociology, biology, and of course, computer science. In all these applications, a close study of the formulation of the problem in the game theory perspective shows a strong inclination to work from existing values, to consider only currently contending parties and options, and in other ways, to exclude significant redefinitions of the problems at hand. This introductory chapter explores these and forms a basis for the rest of the book.

Economic Approach for Network Management

It is not surprising that researchers in network technology are utilizing ideas from the field of economics since it provides the conceptual understanding of underlying constructs such as usage and resource allocation. Proper resource allocation plays a key role in improving network performance. There are two primary approaches to economic resource allocation: quantity limits and pricing. Economic approaches can provide principles in situations and provide valuable guidelines and analysis. A concerted effort is needed from academia, the computer industry, network service providers, and businesses involved in electronic commerce to design new mechanisms for network operations that will be suitable for a new generation network applications. This chapter explores this economic approach for network management.

Game Theory for Wireless Network Resource Management

Computer network bandwidth can be viewed as a limited resource. The users on the network compete for that resource. Their competition can be simulated using game theory models. No centralized regulation of network usage is possible because of the diverse ownership of network resources. Therefore, the problem is of ensuring the fair sharing of network resources. If a centralized system could be developed which would govern the use of the shared resources, each user would get an assigned network usage time or bandwidth, thereby limiting each person's usage of network resources to his or her fair share. As of yet, however, such a system remains an impossibility, making the situation of sharing network resources a competitive game between the users of the network and decreasing everyone's utility. This chapter explores this competitive game.

Game Theory for Wireless Ad Hoc Networks

An ad hoc network typically refers to any set of networks where all devices have equal status on a network and are free to associate with any other ad hoc network device in link range. In particular, ad hoc network often refers to a mode of operation of IEEE 802.11 wireless networks. A wireless ad hoc network is a decentralized type of wireless network. The network is ad hoc because it does not rely on a pre-existing infrastructure, such as routers in wired networks or access points in managed (infrastructure) wireless networks. The decentralized nature of wireless ad hoc networks makes them suitable for a variety of applications where central nodes cannot be relied on and may improve the scalability of networks compared to wireless managed networks, though theoretical and practical limits to the overall capacity of such networks have been identified. This chapter explores this.

Game-Based Control Mechanisms for Cognitive Radio Networks

Comprehensive control mechanism in cognitive radio networks is an important research topic within the scope of empowering cognitive radio functionality in beyond-4G mobile networks. Providing control mechanism for secondary users without interference with primary users is an ambitious task, which requires innovative management architecture designs and routing solutions. Operational challenges such as opportunistic spectrum access, solving problems related to spectrum and network heterogeneities, and requests for the provisioning of Quality-of-Service to different applications must be resolved. As part of a novel management architecture, the control mechanism advances a new approach for cognitive radio networks. We explore this in this chapter.

Game Paradigm for Wired Networks

There are a great number of situations in which a many agent system self-organizes by coordinating individual actions. Such coordination is usually achieved by agents with partial information about the system, and in some cases optimizing utility functions that conflict with each other. A similar situation is found in many network situations. An example of a frustrated multi-agent system is given by the evolutionary minority game in which many players have to make a binary choice and the winning option is the one made by the minority. In evolutionary minority game, players make decisions by evaluating the performance of their strategies from past experience, and hence, they can adapt. The players have access to global information, which is in turn generated by the actions of the agents themselves. As the game progresses, non-trivial fluctuations arise in the agents' collective decisions – these can be understood in terms of the dynamical formation of crowds consisting of agents using correlated strategies. This chapter explores the game paradigm for wired networks.