CCNY Lecture Series on Computer Vision, Robotics and Human-Computer Interaction


Title: Energy-efficient, Fault-tolerant Collaborative Processing in
Sensor Networks

Professor Hairong Qi
Department of Electrical and Computer Engineering
The University of  Tennessee, Knoxville

Date: Wednesday, November 16, 2005
Time:  12:30 PM - 1:30 PM
Room: Steinman Hall, Room T-623

Abstract

Sensors are considered the last missing link between the  Internet and the physical world. A sensor network forms a loosely-coupled distributed environment where collaborative processing among multiple sensor nodes is essential in order to compensate for each other's limited capability in sensing, processing, power supply, and to tolerate faults. The extremely constraint resources of sensor networks have presented unique challenges to collaborative processing, the biggest of which is the contradictory requirements between energy efficiency and fault tolerance. While energy-efficient approaches try to limit the redundancy such that minimum amount of energy is required for fulfilling a certain task, redundancy is needed for providing fault tolerance since sensors might be faulty, malfunctioning, or even malicious. A balance has to be struck between these two objectives.

This talk discusses an integrated system design that tackles the unique challenges presented by sensor networks. This design concerns not only the development of effective processing algorithms, it also studies supporting computing paradigms and protocols which play an important role in facilitating the collaborative processing.

Biography

Hairong Qi received her Ph.D. degree in Computer Engineering from North Carolina State University (NCSU) in 1999, B.S. and M.S. degrees in Computer Science from Northern JiaoTong University, Beijing, P. R. China in 1992 and 1995 respectively. She is now an Associate Professor in the Department of Electrical and Computer Engineering at the University of  Tennessee, Knoxville. Her current research project are in the areas of collaborative signal and information processing in sensor networks, hyperspectral image analysis, and automatic target recognition. Dr. Qi's research is supported by NSF, DARPA, ONR, U.S. Army Space and Missile Defense Command, and U.S. Army Medical Research and Materiel Command.

Dr. Qi received the Science Alliance Faculty Award from UT and Oak Ridge National Lab in 2001, the Leon and Nancy Cole Superior Teaching Award from UT College of Engineering in 2003, the Chancellor's Award for Professional Promise in Research and Creative Achievement in 2004, and the NSF CAREER award in 2005. She has published over 60 technical papers in archival journals and refereed conference proceedings, including a co-authored book in Machine Vision. Dr. Qi serves on the editorial board of Sensor Letters and is the Associate Editor for Computers in Biology and Medicine. She co-edited a special issue on Distributed Sensor Networks for Real-Time Systems with Adaptive Reconfiguration of Journal of Franklin Institute. Dr. Qi is a senior member of IEEE and member of  Sigma Xi and AAAI.


The lecture series is supported by CCNY School of Engineering, and a planning grant from NSF Minority Institutional Infrastructure program.