In this work an iterative solution to build a network lifetime-preserving sampling strategy for WSNs is presented. The paper describes the necessary steps to reconstruct a graph from application data. Once the graph structure is obtained, a sampling strategy aimed at finding the smallest number of concurrent sensors needed to reconstruct the data in the unsampled nodes within a specific error bound, is presented. An iterative method then divides the sensor nodes into sets to be sampled sequentially to increase lifetime. Results on a real-life dataset show that the reconstruction RMSE can be easily traded off for a larger number of disjoint sampling sets which improve the network lifetime linearly.
@article{arxiv.1906.10453,
title = {Energy Efficient WSN: a Cross-layer Graph Signal Processing Solution to Information Redundancy},
author = {Alessandro Chiumento and Nicola Marchetti and Irene Macaluso},
journal= {arXiv preprint arXiv:1906.10453},
year = {2019}
}