A censoring strategy for decentralized estimation in energy-constrained adaptive diffusion networks

This paper presents a censoring strategy for distributed estimation over adaptive networks in scenarios where energy resources are limited. Sensors apply selective communication policies in order to save energy for being able to transmit more important information later. Simulation results show an enhancement in network lifetime, by reducing communication processes among nodes with a slightly degraded result, compared with energy unconstrained schemes.