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宁夏师范大学数学与计算机科学学院,宁夏 固原 756099
Received:12 October 2025,
Revised:2025-11-07,
Accepted:09 February 2026,
Online First:24 September 2026,
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李胜锋,田彦山,马旭等.基于多策略融合改进蛇优化算法的WSN覆盖优化研究[J].物联网学报,
Li Shengfeng,Tian Yanshan,Ma Xu,et al.WSN coverage optimization based on an improved snake optimizer with multi-strategy integration[J].Chinese Journal on Internet of Things,
李胜锋,田彦山,马旭等.基于多策略融合改进蛇优化算法的WSN覆盖优化研究[J].物联网学报, DOI:10.11959/j.issn.2096-3750.WLW25156.
Li Shengfeng,Tian Yanshan,Ma Xu,et al.WSN coverage optimization based on an improved snake optimizer with multi-strategy integration[J].Chinese Journal on Internet of Things, DOI:10.11959/j.issn.2096-3750.WLW25156.
为优化无线传感器网络(wireless sensor network,WSN)节点随机部署所导致的覆盖空洞、分布不均,以及能效低等问题,提出了一种多策略融合改进蛇优化(multi-strategy snake optimizer,MSSO)算法。首先,采用Tent混沌映射与改进对立学习策略生成高质量初始种群,以提升初始解的质量;其次,引入随机—精英交替引导机制,用于平衡并增强算法的全局搜索能力;再次,在开发阶段进一步融合自适应量子竞争纠缠与遗传表观调控机制,旨在增强种群多样性并加速收敛;最后,采用动态适应度排名策略,自适应调整种群选择压力。仿真实验结果表明,与3类改进算法相比,MSSO算法在网络覆盖率与节点分布均匀性方面均表现出更优性能,为解决WSN覆盖优化问题提供了一种有效的解决方案。
To address the issues of coverage holes
uneven node distribution
and low energy efficiency caused by random node deployment in wireless sensor networks (WSN)
a multi-strategy snake optimizer (MSSO) algorlthm was proposed. Firstly
Tent chaotic mapping and an improved opposition-based learning strategy were employed to generate a high-quality initial population. Secondly
a random-elite alternating guidance mechanism was designed to enhance the exploration capability of the algorithm. Subsequently
adaptlve quantum competitive entanglement and genetic epigenetic regulation mechanisms were introduced during the exploitation phase to increase population diversity and improve convergence. Finally
a dynamic fitness ranking strategy was ada pted to adaptively adjust the selection pressure. Simulation results demonstrated that
when compared with three types of improved algorithms
MSSO exhibited superior performance in terms of both network coverage rate and node distribution uniformity
thereby providing an effective solution for WSN coverage optimization.
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