On exploiting spatial correlation for energy harvesting wireless sensor networks

Abstract

Wireless Sensor Network (WSN) is a set of inexpensive densely deployed sensor nodes with limited functionalities and scarcity in energies. The observations of sensors are forwarded directly to the Base Station (BS). In densely deployed sensors, sensing data are likely to be highly correlated in space domain, which produces unfavorable redundant readings and wasting in energy. In this paper, we propose an Event Distortion-Based Node Selection (EDNS) algorithm which exploits spatial correlation for reducing inessential sensor nodes that have correlated readings for improving Energy-Efficiency (EE) with acceptable distortion level. Furthermore, we derive a theoretical framework of distortion function for single-hop communication model to observe the advantages from energy harvesting to the accuracy level. Furthermore, the trade-off between energy consumption and distortion level is investigated.