Monday, March 28, 12:00-1:00 pm, Mudd 535
Abstract: We consider a coalition network where multiple groups are interconnected via wireless links. Gateway nodes are designated by each domain to achieve a network-wide interoperability. Coupled by inter-domain communication cost, the optimal gateway selection for one single domain depends on the gateway selections of other domains and vice versa. We investigate the interactions of gateway selections by multiple domains from a potential game perspective. The equilibrium inefficiency in terms of price of stability is characterized under various conditions. In addition, we examine the well-established equilibrium selective learning algorithm B-logit and show that B-logit is a special case of a general family of algorithms, denoted by $\Gamma$ collectively. A novel learning algorithm named MAX-logit is proposed, which retains the favorable equilibrium selection property with the provably fastest convergence speed than any other algorithms in $\Gamma$, and can be applied to many other applications of potential games.
Speaker Biography: Yang Song is a post-doctoral research staff in Wireless Networking Research Group at IBM Research. He received his Ph.D. degree in Electrical and Computer Engineering at the University of Florida in 2010. His research interests are modeling, analysis, dynamic control and stochastic optimization of communication networks. He is currently working on the International Technology Alliance (ITA) program and resource allocation in cloud computing funded by NIST.