A Graph-based Strategic Sensor Deployment Approach for k-coverage in WSN

TL;DR

This paper introduces a graph-based sensor deployment method for wireless sensor networks that optimizes coverage and reduces sensor density, especially in remote areas, by modeling the problem with graph theory.

Contribution

It presents a novel sensor placement approach that decreases sensor density and number compared to existing methods, enhancing efficiency and reliability.

Findings

Fewer sensors are needed for effective coverage.

Numerical results validate the efficiency of the proposed approach.

Parameter selection impacts system performance positively.

Abstract

This paper studies a graph-based sensor deployment approach in wireless sensor networks (WSNs). Specifically, in today's world, where sensors are everywhere, detecting various attributes like temperature and movement, their deteriorating lifetime is indeed a very concerning issue. In many scenarios, these sensors are placed in extremely remote areas, where maintenance becomes challenging. As a result, it is not very wise to depend on a single sensor to obtain data from a particular terrain or place. Hence, multiple sensors are deployed in these places, such that no problem arises if one or few of them fail. In this work, this problem of intelligent placement of sensors is modelled from the graph theoretic point of view. We propose a new sensor deployment approach here, which results in lesser sensor density per unit area and less number of sensors as compared to the existing benchmark schemes. Finally, the numerical results also support our claims and provide insights regarding the selection of parameters that enhance the system performance.