Coverage optimization strategy for 3D wireless sensor network based on adaptive inertia weight Arctic Puffin Optimization Algorithm
Year: 2025
Type: article
Abstract: A multi-strategy improved Arctic Puffin Optimization Algorithm (CAAPO) based node coverage optimization approach is provided to tackle the problems of unequal node deployment and low coverage in wireless sensor networks (WSNs). Drawing inspiration from the species’ survival strategies in polar environments, the methodology incorporates three key enhancements: Tent chaotic mapping for initial solution refinement, lens imaging inversion mechanisms to prevent premature convergence through population diversification, and adaptive inertia weighting for balanced exploration-exploitation dynamics across optimization phases. Empirical validation through CEC2017 benchmarks and engineering simulations demonstrates CAAPO’s efficacy in nodal deployment optimization. Implementation within sensor coverage models achieves maximal coverage through strategic node positioning, exhibiting superior spatial distribution uniformity compared to conventional methods. The algorithm demonstrates operational efficiency through minimized computational overhead and energy expenditure, thereby enhancing network longevity in resource-constrained environments.
DOI: 10.1093/jcde/qwaf111
Authors: Xiangkun Wang, Li Cao, Zhengwei Zhang, Yinggao Yue, Tao Zhang, Zihui Wang
Institution: Wenzhou University of Technology
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,650
OpenAlex ID: W4415282966