Traditional network optimization focuses on a single control objective in a network populated by obedient users and limited dispersion of information. However, most of today's networks are large-scale with lack of access to centralized information, consist of users with diverse requirements, and are subject to dynamic changes. These factors naturally motivate a new distributed control paradigm, where the network infrastructure is kept simple and the network control functions are delegated to individual agents which make their decisions independently ("selfishly"). The interaction of multiple…mehr
Traditional network optimization focuses on a single control objective in a network populated by obedient users and limited dispersion of information. However, most of today's networks are large-scale with lack of access to centralized information, consist of users with diverse requirements, and are subject to dynamic changes. These factors naturally motivate a new distributed control paradigm, where the network infrastructure is kept simple and the network control functions are delegated to individual agents which make their decisions independently ("selfishly"). The interaction of multiple independent decision-makers necessitates the use of game theory, including economic notions related to markets and incentives.This monograph studies game theoretic models of resource allocation among selfish agents in networks. The first part of the monograph introduces fundamental game theoretic topics. Emphasis is given to the analysis of dynamics in game theoretic situations, which is crucial for design and control of networked systems. The second part of the monograph applies the game theoretic tools for the analysis of resource allocation in communication networks. We set up a general model of routing in wireline networks, emphasizing the congestion problems caused by delay and packet loss. In particular, we develop a systematic approach to characterizing the inefficiencies of network equilibria, and highlight the effect of autonomous service providers on network performance. We then turn to examining distributed power control in wireless networks. We show that the resulting Nash equilibria can be efficient if the degree of freedom given to end-users is properly designed.Table of Contents: Static Games and Solution Concepts / Game Theory Dynamics / Wireline Network Games / Wireless Network Games / Future Perspectives
Produktdetails
Produktdetails
Synthesis Lectures on Learning, Networks, and Algorithms
Asuman Ozdaglar received the B.S. degree in electrical engineering from the Middle East Technical University, Ankara, Turkey, in 1996, and the S.M. and the Ph.D. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology, Cambridge, in 1998 and 2003, respectively. Since 2003,she has been a member of the faculty of the Electrical Engineering and Computer Science Department at the Massachusetts Institute of Technology, where she is currently the Class of 1943 Associate Professor. She is also a member of the Laboratory for Information and Decision Systems and the Operations Research Center. Her research interests include optimization theory, with emphasis on nonlinear programming and convex analysis, game theory, with applications in communication, social, and economic networks, and distributed optimization and control. She is the co-author of the book entitled "Convex Analysis and Optimization" (Athena Scientific, 2003). Professor Ozdaglar is the recipient of a Microsoft fellowship, the MIT Graduate Student Council Teaching award, the NSF Career award, and the 2008 Donald P. Eckman award of the American Automatic Control Council. She served on the Board of Governors of the Control System Society in 2010. She is currently the chair of the working group Game-Theoretic Methods in Networks under the Technical Committee Networks and Communications Systems of the IEEE Control Systems Society and serves as an associate editor for the area Optimization Theory, Algorithms and Applications for the Asia-Pacific Journal of Operational Research. Ishai Menache received his PhD degree in Electrical Engineering from the Technion, Israel Institute of Technology, in 2008. Prior to his graduate studies, he worked for a couple of years in Intel, as an engineer in the networks communication group. Until recently, he was a postdoctoral associate at the Laboratory for Information and Decision Systems in MIT. He is currently a visiting researcher atMicrosoft Research New England, focusing on pricing and resource allocation aspects of Cloud Computing. Dr. Menache's broader areas of interest include communication networks, game theory and machine learning. He is a recipient of the Marie Curie Outgoing International Fellowship.
Inhaltsangabe
Static Games and Solution Concepts.- Game Theory Dynamics.- Wireline Network Games.- Wireless Network Games.- Future Perspectives.
