Journal of Algorithms and Computation
Open Access

Chaos-Enhanced Superb Fairy-wren Optimization Algorithm for Wireless Sensor Network Coverage

Document Type : Research Paper

Authors

Roozbeh Jalal Kamali
Mohammad Reza Omidi

Department of Computer Science, Shahid Bahonar University of kerman

https://doi.org/10.22059/jac.2025.402499.1240
Abstract
Wireless Sensor Networks (WSNs) play a crucial role in monitoring and surveillance, yet random deployment often causes uneven coverage and redundant sensing. This study introduces a Chaos-Enhanced Superb Fairy-wren Optimization Algorithm (CE-SFOA), which integrates chaotic dynamics through a Cubic map into the position update and parameter control mechanisms. The chaotic modulation enhances population diversity, balances exploration and exploitation, and mitigates premature convergence. Experiments across three deployment scenarios show that CE-SFOA consistently achieves higher coverage and faster convergence than SFOA and seven competing metaheuristics, yielding 5.32–6.65% coverage improvement over the baseline. These findings demonstrate that chaotic modulation is an effective strategy for enhancing metaheuristic performance in WSN coverage optimization.

Keywords

Coverage Optimization
Metaheuristic Algorithms
Chaos Theory
Swarm Intelligence
Chaotic Maps
Journal of Algorithms and Computation
Volume 57, Issue 2
December 2025
Pages 1-24

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