Sensing Models and Its Impact on Network Coverage in Wireless Sensor Network

TL;DR

This paper analyzes how different sensing models and node placement strategies affect the coverage in wireless sensor networks, providing insights for optimizing network deployment.

Contribution

It introduces and compares three sensing models and examines their impact on coverage with both regular and random node distributions.

Findings

Sensing models significantly influence network coverage.

Poisson node distribution affects coverage performance.

Comparison between regular and random placement offers deployment insights.

Abstract

Network coverage of wireless sensor network (WSN) means how well an area of interest is being monitored by the deployed network. It depends mainly on sensing model of nodes. In this paper, we present three types of sensing models viz. Boolean sensing model, shadow-fading sensing model and Elfes sensing model. We investigate the impact of sensing models on network coverage. We also investigate network coverage based on Poisson node distribution. A comparative study between regular and random node placement has also been presented in this paper. This study will be useful for coverage analysis of WSN.