Title: Stochastic Dynamic Programming for Network Resource Allocation
Abstract: Stochastic Dynamic Programming (SDP) is a powerful tool for Markov Decision Processes and Partially Observable MDP (POMDP), etc. However, the commonly used Bellman equation and its corresponding backwards recursion algorithm suffer from prohibitive computational complexity because of the curse of dimensionality. This talk presents an application of the SDP method to wireless network resource allocation and develops a 3-layer decomposition algorithm to achieve global optimum solution with affordable complexity. Numerical results show that the SDP algorithm achieves better look-ahead planning than the greedy algorithm and other heuristic algorithms. Practical applications of the research include radio spectrum sharing, intelligent transportation systems, and underwater wireless sensor networks for structure health monitoring systems.
Speaker Bio: Yahong Rosa Zheng received the Ph.D. degree Carleton University, Ottawa, ONT, Canada, in 2002. From 2003 to 2005, she was an NSERC Postdoctoral Fellow with the University of Missouri-Columbia. Since fall 2005, she has been a faculty member with the Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO, where she is now a Professor. Her research interests include digital signal processing, wireless communications, and wireless sensor networks. She has published more than 60 journal papers and more than 100 conference papers in these areas. She served as technical program Co-Chair for the Wireless Communications Symposium (WCS) of IEEE Globecom 2012 and ICC 2014 and tutorial co-chair for Globecom 2016 and ICC 2017-2018. She serves as Associate Editor for the IEEE Transactions on Vehicular Technology. She is the recipient of an NSF CAREER award in 2009. She has been an IEEE fellow and a Distinguished Lecturer of IEEE Vehicular Technology Society since 2015.