Communications and Signal Processing Seminar

Data Fusion Improves the Coverage of Sensor Networks

Guoliang XingData Fusion Improves the Coverage of Sensor NetworksDepartment of Computer Science and Engineering, Michigan State University

Large-scale wireless sensor networks are increasingly available for mission-critical applications such as security surveillance and environmental monitoring. As an important performance measure of these applications, sensing coverage characterizes how well a sensing field is monitored by a network. Although advanced collaborative signal processing algorithms are adopted by many existing sensor network systems, analytical studies on coverage have been relying on overly simplistic models (e.g., the disc model) that do not capture the stochastic nature of sensing. This gap is mainly caused by the difficulty in understanding the complex impacts of collaborative sensing algorithms on network-level performance.
As the first step to bridging this gap, we proposed an analytical framework for studying the fundamental limits of coverage based on stochastic data fusion models. Data fusion is an established signal processing technique that can improve the performance of detection by combining the data of multiple sensors. This talk describes the scaling laws between coverage, network density, and signal-to-noise ratio for fusion-based sensor networks. I will show that data fusion significantly improves the coverage of a network by exploiting the collaboration among sensors. Our work helps understand the limitations of the previous analytical results and provides insights into the impact of data fusion on the performance of large-scale sensor networks.

Guoliang Xing is an Assistant Professor in the Department of Computer Science and Engineering at Michigan State University. He received the B.S. degree in Electrical Engineering and the M.S. degree in Computer Science from Xi'an Jiaotong University, China in 1998 and 2001, respectively. He received the Doctor of Science degree in Computer Science from Washington University in St. Louis in 2006. Prior to joining Michigan State University, he was on the faculty of Computer Science Department at the City University of Hong Kong. He has served on the technical program committees for a number of international conferences including MobiHoc and RTSS and held several workshop chair positions including Program Co-chairs of the ACM International Workshop on Heterogeneous Sensor and Actor Networks (2008) and the IEEE Workshop on Wireless Ad hoc and Sensor Networks (2008 and 2009). His research interests include Cyber-physical Systems, Wireless Sensor Networks, and Wireless Networking.

Sponsored by

Mingyan Liu