As the need to support high speed data exchange in communication networks grows rapidly, effective and fair sharing of the network resources becomes very important. Today’s communication networks typically involve a large number of users that share the same network resources but may have different and often competing objectives. Network protocols aiming to optimize the performance of such networks typically assume that users are passive and are willing to compromise their own performance for the sake of optimizing the performance of the overall network. However, considering the trend towards more decentralization in the future, it is natural to assume that the users in a large network may take a more active approach and become more interested in optimizing their own individual performances without giving much consideration to the overall performance of the network. Game theory provides the necessary framework and mathematical tools for formulating and analyzing the strategic interactions among network users, or teams of users, of such networks. This presentation focuses on using these frameworks to optimize flow and routing controls for communication networks with competing or cooperating users. The Nash equilibrium, non-inferior Nash equilibrium, and Pareto optimal strategies will be stressed.
Dr. Sahin received his M.S. degree in electrical and computer engineering (ECE) from the University of Florida in 2001, and Ph.D. degree in ECE from the University of Pittsburgh in 2006. Between 2009 and 2013, he joined NIST, the National Institute of Standards and Technology, where he engaged in using optimization theory for data analysis for neutron scattering experiments at the NIST Center for Neutron Research Division and developed a time delay estimation method at the Mathematical and Computational Science Division. Currently, he is a visiting assistant professor at the Electrical Engineering Department at Texas A&M University – Kingsville.