Flexible WSN data gathering through energy-aware adaptive sensing

Abstract

The multitude of Wireless Sensor Networks (WSNs) environments, being typically resource-constrained, clearly benefit from properties such as adaptiveness and energy-awareness, in particular, in presence of demanding data gathering applications. This paper proposes a self-adaptive, energy-aware sensing scheme for WSNs (e-LiteSense), which aims at self-adjusting the data gathering process to each specific WSN context, capturing accurately the behaviour of physical parameters of interest yet reducing the sensing overhead. The adaptive scheme relies on a set of low-complexity rules capable of auto-regulate the sensing frequency according to the parameters variability and energy levels. The proof-of-concept resorts to real-world datasets to provide evidence of e-LiteSense ability to optimise the data gathering process according to energy levels, improving the trade-off between accuracy and WSN lifetime.