Probabilistic Methods For Dynamic Node Population Management In Sensornets

Sensornets provide coverage of physical phenomena over extended periods, perhaps months or years. However, active nodes may deplete finite batteries within days, and are prone to failure. The sensornet application may require a given number of active nodes within each region to provide appropriate sensor redundancy and processing capacity. If many nodes are deployed, at any given time a smaller working set of the correct size can be selected for duty. In this paper we present a lightweight approach to active population management. An omniscient overview of network state is not required, and expensive communication activity is minimised. Probabilistic methods are employed, ensuring that individual nodes can make appropriate decisions using only locally available information.