Measurement and Monitoring in Wireless Sensor Networks

May 4, 2004
Jerry Zhao | USC

Wireless sensor network is one of the emerging technology trends in the coming decades. These networks will consist of a large collection of embedded sensors, collaboratively providing robust distributed sensing, storage, and communication services. We study the problem of measurement and monitoring in wireless sensor networks: Systematic measurement methodology is one important component in the iterative process of system design and evaluation. A self monitoring infrastructure that indicates failures and abnormalities, is a key component of any operational sensor network system.

I will first illustrate our measurement methodology by a fine-grain systematic measurement on packet delivery performance in wireless sensor networks. We show that how those experiments are carefully designed to cover a wide range of experiment parameters and metrics, and the primary findings and their impacts on system design and evaluation. I will then present a new architecture to collect system status in different spatial or temporal details. Shown in the design of two major components in this architecture, sensor network scans and digests, we identify several design principles to ensure efficient and robust monitoring: in-network aggregation to push data processing into the network, vertical integration to reduce unnecessary messaging overhead, and localized signaling to increase tolerance to routing failures.

Speaker Details

Jerry Zhao is a Ph.D. candidate in Computer Science Department at University of Southern California, co-advised by Professor Ramesh Govindan and Professor Deborah Estrin. He received his M.S. in Computer Science from University of Southern California, and his B.S. from Fudan University respectively. His current research focus is in the area of wireless ad hoc sensor networks, especially on the issues associated with the design of scalable, energy-efficient monitoring protocols, and the measurement methodology for sensor networks. He received the Best Student Paper award at the First ACM Conference on Embedded Networked Sensor Systems (Sensys’03).