The dramatic growth in world-wide demand for communication services has highlighted the need for efficient and economically viable resource allocation strategies within communication networks. In recent years, a mathematical theory has emerged to provide a framework within which resource allocation problems can be properly analyzed. This framework is based on the theory of optimization, with particular emphasis on distributed algorithms. In this short course, we present the fundamental theory and essential applications of this framework. We start with discussion of wired networks, where the optimization framework provides the theoretical basis for optimal routing and TCP congestion control schemes. We then move to wireless networks, where the optimization framework is expanded to solve the problems of multi-user interference and energy limitations of mobile nodes. We conclude with discussion of challenging research directions within this evolving framework.
Edmund Yeh was born in Shanghai, China, in 1971. He received his B.S. in Electrical Engineering with Distinction from Stanford University in 1994, M.Phil in Engineering from the University of Cambridge in 1995, and Ph.D. in Electrical Engineering and Computer Science from MIT in 2001. Since July 2001, he has been on the faculty at Yale University, New Haven, Connecticut, where he is currently an Associate Professor of Electrical Engineering and Computer Science. Dr. Yeh is a recipient of the Army Research Office (ARO) Young Investigator Program (YIP) Award (2003), the Winston Churchill Scholarship (1994), the National Science Foundation and Office of Naval Research Fellowships (1994) for graduate study, the Frederick E. Terman Award from Stanford University (1994) and the Barry M. Goldwater Scholarship from the United States Congress (1993). He has served on the Technical Program Committees for IEEE Infocom (2005, 2006) and IEEE Globecom (2004). Dr. Yeh is a member of Phi Beta Kappa, Tau Beta Pi, and IEEE. He has been visiting faculty at MIT, Princeton University, University of California at Berkeley, and Swiss Federal Institute of Technology, Lausanne.