Inference and Management Network Parameters in Wireless Sensor Networks

PhD Thesis Proposal Defence


Title: "Inference and Management Network Parameters in Wireless Sensor Networks"

by

Miss Xiaoxu LI


Abstract:

A large-scale sensor network typically consists of numerous low-cost and 
resources constrained sensor nodes working in a self-organizing manner. Being 
embedded in the physical world, wireless sensor networks (WSNs) present a wide 
range of failures, due to environment conditions, hardware limitations and 
software uncertainties, and so on. Once deployed, the interactivity of a WSN 
greatly decreases, and network managers must investigate network behaviors with 
limited visibility into the application. Based on a real world environment 
monitoring sensor network project CitySee, this proposal address three key 
aspects for network parameters management in wireless sensor networks, i.e., 
injecting performance related time-varying metrics into each sensor node, and 
collecting these metrics to enhance network visibility, providing a more 
practical and efficient diagnosis model and topology shaping method for time 
synchronization in wireless sensor networks. Through intensive simulations and 
real world implementations, I evaluate the performance of the proposed methods 
in a real system and verify the applicability. The results show that the 
proposed approaches are effective and efficient.


Date:			Monday, 12 August 2013

Time:                   2:00pm - 4:00pm

Venue:                  Room 3501
                         lifts 25/26

Committee Members:	Dr. Yunhao Liu (Supervisor)
 			Prof. Gary Chan (Chairperson)
 			Dr. Lei Chen
 			Dr. Ke Yi


**** ALL are Welcome ****