Adaptive Probing and Communication in Sensor Networks

Sensor networks consist of multiple low-cost, autonomous, ad-hoc sensors, that periodically probe and react to the environment and communicate with other sensors or devices. A primary concern in the operation of sensor networks is the limited energy capacity per sensor. As a result, a common challenge is in setting the probing frequency, so as to compromise between the cost of frequent probing and the inaccuracy resulting from infrequent probing. We present adaptive probing algorithms that enable sensors to make effective selections of their next probing time, based on prior probes. We also present adaptive communication techniques, which allow reduced communication between sensors, and hence significant energy savings, without sacrificing accuracy. The presented algorithms were implemented in Motes sensors and are shown to be effective by testing them on real data.