Sensor Network Tomography

Abstract

Wireless sensor networks have been attracting increasing research interest given the recent advances in miniaturization and low-cost, low-power design. Consisting of a large collection of small wireless, low-power, unattended sensors and/or actuators, wireless sensor network technology poses its unique design challenges. Given their unattended nature and their complexity, it is critical that the users be given continuously updated indications of the sensor network health, i.e., explicit knowledge of the overall state of the sensor network after deployment. We call such indications of network health scans. Such macroscopic view of resources or activities in large sensor networks can provide users early warning of system failure, aid in incremental deployment of sensors, or tuning sensor collaboration algorithms.Monitoring wireless sensor networks leads to different challenges compared to existing diagnosis protocols for the Internet, or monitoring systems in other domains such as telecommunication networks, or power generation systems. The monitoring system should introduce minimal impact on network lifetime, scale with network size, yet preserve the fidelity of the overall picture. We propose Sensor Network Tomography to construct abstracted scans of sensor network health by applying localized algorithms in sensor networks for energy-efficient in-network aggregation of local representations of scans. Rather than collect detailed state information from each individual sensor node and then process centrally, this technique builds a composite scan by combining local scans piecewise on their way towards a collecting point. When local scans are aggregated, detailed information at an individual node may be lost. However, the compactness of such an abstracted representation can reduce the communication and processing cost significantly.