Abstract: We consider optimal stochastic control of wireless networks with time varying channels and adaptive transmission rates. First, an energy-aware scheduling and routing algorithm is constructed and shown to have average power expenditure that is arbitrarily close to the minimum power required for network stability. Proximity to the optimal solution is determined by a control parameter V affecting a tradeoff in end-to-end network delay. Next, we develop an optimally fair admission strategy for the case when input traffic exceeds network capacity. Finally, we focus on ad-hoc mobile networks with a simple cell-partitioned structure, and show that replicated packet transfers can dramatically reduce network delay, achieving an optimal throughput/delay tradeoff. All algorithms have distributed implementations and do not require knowledge of traffic rates or channel statistics.

Biography: Michael J. Neely received the B.S. degrees in both Electrical Engineering and Mathematics from the University of Maryland, College Park, in 1997. He then received a 3 year Department of Defense NDSEG Fellowship for graduate study at the Massachusetts Institute of Technology, where he received an M.S. degree in EECS in 1999 and a Ph.D. in 2003. During the Summer of 2002, he worked as an intern in the Distributed Sensor Networks group at Draper Labs in Cambridge. In January 2004 he joined the faculty of Electrical Engineering at the University of Southern California, where he is currently an assistant professor. His research interests are in the areas of satellite and wireless networks, ad-hoc wireless networks, and queueing theory. Michael is a member of Tau Beta Pi and Phi Beta Kappa.

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