An Efficient Method for Solving the Best Coverage Path Problem in Homogeneous Wireless Ad-Hoc Sensor Networks

Abstract

Barrier coverage is a well-established model within the domain of Wireless Ad-hoc Sensor Networks (WASNs), which finds substantial utility in numerous military and security applications within the Internet of Things (IoT). It is particularly pertinent for monitoring and detecting objects in motion across the sensing field. This research paper delves into the central aspect of barrier coverage within WASNs, with a specific focus on the maximal exposure path (MaEP) problem, a problem proven to be NP-Hard. The MaEP problem entails the pursuit of an optimal coverage path that either conserves energy or minimizes energy consumption while maintaining a short traversal distance. Prior studies in this domain predominantly relied on problem formulations based solely on Euclidean distance metrics, often addressed through computational geometry methodologies. However, this approach encounters significant challenges in scenarios characterized by large-scale, intricate, and highly sophisticated WASNs. To surmount this limitation, our research first casts the MaEP problem within the framework of the integral of sensing field intensity. Subsequently, we introduce a modified particle-swarm-optimization-based algorithm denoted as MaEP-PSO, meticulously designed to efficiently address the MaEP problem. To gauge the efficacy of this proposed algorithm, we conduct an extensive series of experiments and present comprehensive experimental results.