Events Calendar

Inferring Network Internal State via Network Tomography

Speaker: Dr. Ting He, IBM

Talk Title: Inferring Network Internal State via Network Tomography

Abstract: Timely and accurate knowledge of network internal state (e.g., delay/loss/jitter on links) is essential to efficient network operation and resource allocation. Obtaining such knowledge is, however, a highly nontrivial task in large-scale heterogeneous networks, where the existence of heterogeneous domains due to the difference in communication technology, protocol, ownership, and/or policy makes it difficult for a single monitoring system to receive global support throughout the network.

In this talk, I will review a promising approach for monitoring such networks by inferring the internal network state (e.g., link delay) from end-to-end measurements (e.g., path delay) taken between monitors, known as network tomography. The focus will be given to a key challenge in applying network tomography, called "lack of identifiability", i.e., the measurements cannot uniquely determine the network state. In contrast to previous works that resort to best-effort heuristics, I aim at guaranteeing identifiability via carefully designed measurements. Specifically, I (i) establish the fundamental condition on the network topology and monitor placement to achieve identifiability, (ii) develop the optimal monitor placement algorithm that guarantees identifiability using a minimum number of monitors, (iii) develop an efficient path construction algorithm that finds a set of linearly independent paths, whose measurements can uniquely determine the link metrics, and (iv) design probing experiments that allocate probes among the paths to minimize the error in estimating link parameters in the case of random link metrics. The above results are selected from publications at ICDCS'13, IMC'13, TON'14, and SIGMETRICS'15, and have won several best paper awards and nomination.


Biography: Ting He is a Research Staff Member at IBM T.J. Watson Research Center, where she has worked for over 8 years in the Wireless Network Research Group and the Network Analytics Research Group. Before that, she was a Graduate Research Assistant at the Adaptive Communications and Signal Processing Group at Cornell University in 2003-2007, where she received the Ph.D. degree in Electrical Engineering.

At IBM, Dr. He has worked as a primary researcher and task lead in several major research programs including the International Technology Alliance (ITA) program funded by US ARL and UK MoD, the Measurement Science in Cloud Computing program funded by NIST, and the Social Media in Strategic Communication (SMISC) program funded by DARPA. Her work aims at applying mathematical principles developed in signal processing, graph theory, information theory, stochastic optimization, and online learning to practical problems arising in the broad areas of network monitoring, performance analysis, and optimization.

Dr. He is a senior member of IEEE. She has served as the Membership Co-chair of ACM N2Women and the TPC of many communications and networking conferences, including IEEE INFOCOM, IEEE SECON, IEEE/ACM IWQoS, IEEE WiOpt, IEEE MILCOM, IEEE ICNC, IFIP Networking, etc. She received the Outstanding Contributor Award from IBM Research in 2009 and 2013, and the Most Collaboratively Complete Publications Award from ITA in 2015. Her papers won the Best Paper Award at IEEE ICDCS'13, the Outstanding Student Paper Award at ACM SIGMETRICS'15, the Best Paper Nomminee at ACM IMC'13, and the Best Student Paper Award at IEEE ICASSP'05. She received the Distinguished TPC Member Award for her service at IEEE INFOCOM'16. In school, she was an Outstanding College Graduate of Beijing and and an Outstanding Gradudate of Peking University in 2003, and a winner of the Excellent Student Awards and scholarships from Peking University from 1999 to 2002.


Host: Professor Bhaskar Krishnamachari

Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

Audiences: Everyone Is Invited

Contact: Theodore Low