Center for Embedded Network Sensing

It is important to have continuously updated information about network resources and application activities in a wireless sensor network after it is deployed in an unpredictable environment. Such information can help notify users of resource depletion or abnormal activities. However, constrained by the low user-to-node ratio, limited energy and bandwidth resources, it is infeasible to extract state of each individual node. In this paper, we propose an approach to construct abstracted scans of sensor network health by applying in-network aggregation of network state. Specifically, we design a residual energy scan which approximately depicts the remaining energy distribution within a sensor network. Simulations show that our approach has good scalability and energy-efficiency characteristics, compared to continuously extracting the residual energy level individually from each node.