Mitigating Dead Node Impact on Coverage and Connectivity in Wireless Sensor Networks Using a Hybrid Approach
Year: 2025
Type: article
Abstract: Wireless sensor networks’ coverage and efficient connectivity are pivotal for reliable data collection and communication. However, dead nodes, resulting from hardware failure or power depletion, can affect coverage and connectivity, leading to information loss and degraded performance. Previous research in the same context indicates the need for further investigation to achieve optimal trade-offs in network resource allocation. This research introduces a hybrid Artificial Bee Colony-Sequential Re-connectivity and Coverage Algorithm (ABC-SRCA) approach, combining the ABC algorithm with a developed SRCA. The ABC algorithm adjusts sensor node placement to maximize the coverage and minimize holes, while the SRCA algorithm restores connectivity by reconnecting the network when nodes fail. The approach uses probabilistic selection to explore various solutions, making the approach adaptive to diverse scenarios. The simulation outcomes indicate that the ABC-SRCA method enhances coverage accuracy by up to 30% compared to ABC and SRCA when they are used separately. In addition, the rate of connectivity error detection decreases by about 25%, highlighting the method’s effectiveness in dynamic network conditions. The approach also surpasses existing methods, including Genetic Algorithms and Sensing Radius Adaptive Coverage Control (SRACC), by achieving coverage level up to 98% while conserving resources. The ABC-SRCA achieves better energy consumption than Particle Swarm Optimization (PSO) and PSO Voronoi Diagram and achieves competent energy when compared with SRACC. The hybrid approach provides an effective solution for ensuring efficient and reliable network operations, supporting the successful deployment of WSNs in diverse applications.
DOI: 10.14500/aro.11710
Author: Omeed K. Khorsheed
Institution: Koya University
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409523220