ASample: Adaptive Spatial Sampling in Wireless Sensor Networks

Abstract—A prominent application of Wireless Sensor Networks is the monitoring of physical phenomena. The value of the monitored attributes naturally depends on the accuracy of the spatial sampling achieved by the deployed sensors. The monitored phenomena often tend to have unknown spatial distributions at pre-deployment stage, which also change over time. This can detrimentally affect the overall achievable accuracy of monitoring. Consequently, reaching an optimal (accuracy driven) static sensor node deployment is generally not possible, resulting in either under- or over-sampling of signals in space. Our goal is to provide for adaptive spatial sampling. The key challenges consist in identifying the regions of over- or under-sampling and in suggesting the appropriate countermeasures. In this paper, we propose a Voronoi based adaptive spatial sampling (ASample) solution. Our approach removes unnecessary samples from regions of over-sampling and generates additional new sampling locat...

• Type: Conference
• Year: 2010
• Where: SUTC
• Authors: Piotr Szczytowski, Abdelmajid Khelil, Neeraj Suri
• Keywords: Adaptive Spatial Sampling, Sensor Networks, Spatial Sampling, SUTC 2010