March 29, 2010
Hosted by: Prof. Gil Zussman
Speaker: Dr. Ting He, IBM Research
Mission-critical MANETs can impose severe challenges on communications. In applications such as military tactical operations and search-and-rescue operations, task nodes can cover a large field with little or no connectivity between them due to obstacles, limited range, poor channel conditions, etc. Moreover, the mobility of task nodes is dictated by mission needs and may not coincide with the mobility required to provide sufficient contacts. In this talk, we present a solution to this problem using controllable mobile data ferries, with the focus on the mobility control of these ferries. While existing ferry control techniques assume either stationary nodes or complete ferry observation of node locations, we address the more challenging scenario of highly mobile nodes and partial ferry observations. Using the tool of Partially Observable Markov Decision Processes (POMDP), we develop a comprehensive framework where we expand the solution space from predetermined trajectories to control policies that can map ferry observations to navigation actions dynamically. Under this framework, we present an optimal and several efficient heuristic policies. We compare the proposed policies with predetermined control through analysis and simulations with respect to multiple node mobility parameters including speed, locality, activeness, and range of movement. The comparison shows a significant performance gain in cases of high uncertainty. In cases of low uncertainty, we give a sufficient condition under which the predetermined control is optimal.
Ting He is a Research Staff Member in the Networking Technologies group at IBM T.J. Watson Center, Hawthorne, NY. She received the Ph.D. degree from the School of Electrical and Computer Engineering, Cornell University, in 2007 and the B.S. degree in Computer Science from Peking University, China, in 2003. At IBM, Ting works under the International Technology Alliance (ITA) program funded by US ARL and UK MoD, the ARRA program funded by NIST, and other business-related projects on network science and technologies. Previously at Cornell (2003-2007), Ting was a member of the Adaptive Communications & Signal Processing Group (ACSP) under the supervision of Prof. Lang Tong.
Ting is a member of IEEE. She received the Best Student Paper Award at the 2005 International Conference on Acoustic, Speech and Signal Processing (ICASSP). She was an Outstanding College Graduate of Beijing Area and an Outstanding Graduate of Peking University in 2003. She was a winner of the Excellent Student Award of Peking University during 1999-2002 and a recipient of Canon, Sony, and Yang-Wang Academicians scholarships.
Ting has worked on nonparametric change detection and estimation in sensor networks, stepping-stone detection in Internet, and general information flow detection in wireless ad hoc networks. Her recent research includes controlled mobility in communication networks, detection and throughput analysis of clandestine information flows, network optimization in coalition networks, and modeling and control of cloud computing networks. Her general research interests include detection and estimation theory, stochastic control, statistical signal processing, information theory, and network security.