A Coverage-Enhancing Scheme for Heterogeneous Directional Wireless Sensor Networks

Wireless Sensor Networks (WSNs) play a crucial role in applications like environmental monitoring, industrial automation, and smart cities, where effective target coverage is essential for system reliability. However, most existing research on target coverage often assumes homogeneous sensor models. In practice, sensors like radars and cameras in WSNs possess diverse characteristics, including different detection radii, fields of view, and rotation speeds. This discrepancy between the assumptions of existing research and practical situations highlights the need for a more realistic approach. Against this backdrop, this work focuses on the target coverage problem in heterogeneous directional wireless sensor networks. We investigate the problem considering sensors with heterogeneous attributes. We establish a system model for such networks and propose a cluster - based greedy algorithm that prioritizes maximum cost - effectiveness. Through simulations, our proposed method demonstrates a 10 percent improvement in the coverage rate compared to the simple distributed greedy algorithm.