Adaptive Random Sensor Selection for Field Reconstruction in Wireless Sensor Networks

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Executive Summary

Wireless Sensor Networks (WSNs) allow for the sampling of a physical phenomenon over long periods of time and across extended geographical areas. Once reported to a central collecting unit, the samples may be used to re-construct the developing of the physical phenomenon of interest - also referred to as signal or sensor field - in both time and space. Work in information theory shows that a reliable signal reconstruction is possible if a sufficiently large number of nodes sample the signal at sufficiently close time and space intervals.

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