MS defense: Recovering from Soft Node Failures in Wireless Sensor Networks using Neural Networks

MS Thesis Defense

Recovering from Soft Node Failures in
Wireless Sensor Networks using Neural Networks

Shivvasangari Subramani

9:00am Tuesday, 26 April 2011, ITE 346

In the past few years, wireless sensor networks (WSNs) have become important in different applications because of their robustness in hostile environments. WSNs need to perform in a timely manner in the face of interference, attacks, accidents, and failures. Being a battery operated system, there is a trade-off between performance and energy utilization. In this thesis we focus on WSN accuracy and consider ways to improve the performance of WSNs when sensors become damaged, resulting in poor input signal quality. When all other components of the sensor like the processor, memory, and battery are working, our proposed solution is to learn to undo the damage in a node by training on neighbors sensor values.

Thesis Committee:

• Dr. Anupam Joshi
• Dr. Tim Oates (chair)
• Dr. Mohamed Younis