Coverage Hole Recovery in Hybrid Sensor Networks Based on Key Perceptual Intersections for Emergency Communications

Area of Science:

• Computer Science
• Network Engineering
• Wireless Communication

Background:

• Wireless sensor networks (WSNs) face challenges with energy depletion, leading to coverage holes and degraded performance.
• Coverage holes in WSNs compromise data quality, network efficiency, and overall quality of service.
• Effective detection and recovery of coverage holes are critical for reliable WSN operation.

Purpose of the Study:

• To propose an efficient method for detecting and recovering coverage holes in wireless sensor networks.
• To address the issues of energy depletion and network dysfunction caused by coverage holes.
• To enhance the performance and reliability of WSNs through improved coverage management.

Main Methods:

• The proposed method divides the WSN into units and selects representative agent nodes.
• Coverage percentage is accurately calculated to detect coverage holes.
• Particle Swarm Optimization (PSO) is utilized for hole recovery, using key perceptual intersections as initial values.

Main Results:

• The algorithm reduced network energy consumption by 6.68%.
• The distance traveled by mobile nodes decreased by 8.51%.
• The percentage of network hole recovery increased by 2.16% compared to existing algorithms.

Conclusions:

• The developed method effectively detects and recovers coverage holes in WSNs.
• The approach leads to significant improvements in energy efficiency and network coverage.
• This technique offers a promising solution for enhancing the longevity and performance of wireless sensor networks.