Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless Sensor Networks (WSNs) are crucial for applications like intrusion detection and monitoring.
• Radio Signal Strength Indicator (RSSI)-based localization is a common technique in WSNs.
• Existing coverage models (e.g., disk coverage) are often too simplistic for WSN localization, especially for non-disk models like ellipses.

Purpose of the Study:

• To address the challenge of coverage holes in WSNs, specifically for RSSI-based localization techniques employing an elliptical coverage model.
• To propose and evaluate an algorithm for detecting and recovering these coverage holes.

Main Methods:

• The study proposes an algorithm inspired by Voronoi tessellation and Delaunay triangulation.
• This algorithm is designed to identify and fill coverage gaps within the WSN.
• The method specifically targets WSNs with elliptical coverage models.

Main Results:

• The proposed algorithm successfully detects and recovers coverage holes in WSNs.
• Simulation results demonstrate the algorithm's ability to achieve any desired coverage rate, including full 100% coverage.
• The technique enhances the effectiveness of RSSI-based localization in WSNs.

Conclusions:

• The developed algorithm effectively addresses coverage hole issues in WSNs with elliptical coverage models.
• This approach significantly improves the reliability and performance of RSSI-based localization techniques.
• The method offers a scalable solution for achieving comprehensive WSN coverage.