基于多策略融合改进蛇优化算法的WSN覆盖优化研究

李胜锋; 田彦山; 马旭; 张芳琴; 杨金米; 马甜甜; 罗晓丽

doi:10.11959/j.issn.2096-3750.WLW25156

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基于多策略融合改进蛇优化算法的WSN覆盖优化研究

更新时间：2026-09-24

- 基于多策略融合改进蛇优化算法的WSN覆盖优化研究
- WSN coverage optimization based on an improved snake optimizer with multi-strategy integration
- 物联网学报 2026年页码：1-14
- 作者机构：
  
  宁夏师范大学数学与计算机科学学院，宁夏固原 756099
- 作者简介：
  
  李胜锋（2001‒ ），男，宁夏师范大学数学与计算机科学学院硕士生，主要研究方向为智能优化算法、无线传感器网络覆盖优化。
  田彦山（1979‒ ），男，宁夏师范大学数学与计算机科学学院教授、硕士生导师，主要研究方向为并行与分布式计算、嵌入式计算、边缘计算。
  马旭（1970‒ ），男，宁夏师范大学数学与计算机科学学院教授、硕士生导师，主要研究方向为计算机软件与理论、云计算、大数据。
  张芳琴（1982‒ ），女，宁夏师范大学数学与计算机科学学院副教授，主要研究方向为嵌入式系统、无线网联智能系统。
  杨金米（1996‒ ），女，宁夏师范大学数学与计算机科学学院助教，主要研究方向为图像处理、模式识别。
  马甜甜（1998‒ ），女，宁夏师范大学数学与计算机科学学院助教，主要研究方向为LTE、无线网络。
  罗晓丽（1990‒ ），女，博士，宁夏师范大学数学与计算机科学学院副教授、硕士生导师，主要研究方向为模式识别、光学分子图像、目标检测、医学图像分析。
- 基金信息：
  
  国家自然科学基金地区科学基金资助项目(62566048;62262054);宁夏自治区重点研发计划(2023BEG02072);宁夏自然科学基金项目(2025AAC030615)
- DOI：10.11959/j.issn.2096-3750.WLW25156
  中图分类号：
- 收稿：2025-10-12，
  
  修回：2025-11-07，
  
  录用：2026-02-09，
  
  网络首发：2026-09-24，
- 稿件说明：
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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.

摘要

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。

Abstract

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.

关键词

Keywords

references

Tsai C W , Hong T P , Shiu G N . Metaheuristics for the lifetime of WSN: a review [J ] . IEEE Sensors Journal , 2016 , 16 ( 9 ): 2812 - 2831 .

Zaimen K , Brahmia M E A , Moalic L , et al . A survey of artificial intelligence based WSNs deployment techniques and related objectives modeling [J ] . IEEE Access , 2022 , 10 : 113294 - 113329 .

朱洪波 , 尹浩 . 智能化时代的物联网科技与产业发展分析及策略 [J ] . 物联网学报 , 2025 , 9 ( 3 ): 1 - 16 .

Zhu H B , Yin H . Analysis and strategies of IoT technology and industrial development in the intelligent era [J ] . Chinese Journal on Internet of Things , 2025 , 9 ( 3 ): 1 - 16 .

陈江南 , 陈旭彬 , 邓颀 , 等 . 基于ESP8266的智能家居火灾监测系统设计与实现 [J ] . 物联网技术 , 2025 , 15 ( 17 ): 16 - 20, 26 .

Chen J N , Chen X B , Deng Q , et al . Design and implementation of smart home fire monitoring system based on ESP8266 [J ] . Internet of Things Technologies , 2025 , 15 ( 17 ): 16 - 20, 26 .

李守定 , 乔华 , 马世伟 , 等 . 基于温度-降雨双参数的新疆地质灾害预警模型 [J ] . 水利水电技术(中英文) , 2021 , 52 ( 11 ): 207 - 218 .

Li S D , Qiao H , Ma S W , et al . Temperature-rainfall dual parameter-based early warning model for geological disasters in Xinjiang [J ] . Water Resources and Hydropower Engineering , 2021 , 52 ( 11 ): 207 - 218 .

苟平章 , 孙现超 , 毛刚 . 基于改进遗传算法的覆盖空洞修复优化 [J ] . 传感技术学报 , 2020 , 33 ( 12 ): 1800 - 1807 .

Gou P Z , Sun X C , Mao G . Optimization of recovering coverage holes based on improved genetic algorithm [J ] . Chinese Journal of Sensors and Actuators , 2020 , 33 ( 12 ): 1800 - 1807 .

Egwuche O S , Singh A , Ezugwu A E , et al . Machine learning for coverage optimization in wireless sensor networks: a comprehensive review [J ] . Annals of Operations Research , 2023 : 1 - 67 .

Kennedy J , Eberhart R . Particle swarm optimization [C ] // Proceedings of ICNN'95 - International Conference on Neural Networks . Piscataway : IEEE Press , 1995 : 1942 - 1948 .

Mirjalili S , Lewis A . The whale optimization algorithm [J ] . Advances in Engineering Software , 2016 , 95 : 51 - 67 .

Xue J K , Shen B . A novel swarm intelligence optimization approach: sparrow search algorithm [J ] . Systems Science & Control Engineering , 2020 , 8 ( 1 ): 22 - 34 .

陈立万 , 赵尚飞 , 曾蝶 , 等 . 基于混合策略麻雀搜索算法的WSN覆盖优化 [J ] . 电子测量技术 , 2022 , 45 ( 23 ): 174 - 180 .

Chen L W , Zhao S F , Zeng D , et al . WSN coverage optimization based on hybrid strategy sparrow search algorithm [J ] . Electronic Measurement Technology , 2022 , 45 ( 23 ): 174 - 180 .

王振东 , 王建兰 , 王俊岭 , 等 . 融合多策略学习型麻雀搜索算法的UWSN覆盖优化 [J ] . 传感技术学报 , 2024 , 37 ( 8 ): 1424 - 1433 .

Wang Z D , Wang J L , Wang J L , et al . UWSN coverage optimization based on multi-strategy learning sparrow search algorithm [J ] . Chinese Journal of Sensors and Actuators , 2024 , 37 ( 8 ): 1424 - 1433 .

周恺卿 , 杨森宇 , 康棣文 , 等 . 基于改进布谷鸟搜索算法的无线传感器网络覆盖优化 [J ] . 河南理工大学学报(自然科学版) , 2025 , 44 ( 4 ): 48 - 58, 141 .

Zhou K Q , Yang S Y , Kang D W , et al . Coverage optimization in wireless sensor networks based on improved cuckoo search algorithm [J ] . Journal of Henan Polytechnic University (Natural Science) , 2025 , 44 ( 4 ): 48 - 58, 141 .

程仁轩 , 徐凯宏 , 高俊哲 , 等 . 改进蛇算法的无线传感网络覆盖优化研究 [J ] . 火力与指挥控制 , 2025 , 50 ( 7 ): 80 - 87 .

Cheng R X , Xu K H , Gao J Z , et al . Research on optimization of wireless sensor network coverage with improved snake algorithm [J ] . Fire Control & Command Control , 2025 , 50 ( 7 ): 80 - 87 .

李振 , 冯锋 . 基于改进蛇优化算法的WSN覆盖研究 [J ] . 计算机技术与发展 , 2024 , 34 ( 3 ): 89 - 95 .

Li Z , Feng F . Research on WSN coverage based on improved snake optimizer algorithm [J ] . Computer Technology and Development , 2024 , 34 ( 3 ): 89 - 95 .

张勇 , 唐睿哲 , 刘畅 , 等 . 基于改进蛇优化算法的WSN覆盖优化研究 [J ] . 电子测量技术 , 2024 , 47 ( 16 ): 24 - 32 .

Zhang Y , Tang R Z , Liu C , et al . Research on WSN coverage optimization based on improved snake optimization algorithm [J ] . Electronic Measurement Technology , 2024 , 47 ( 16 ): 24 - 32 .

Zaimen K , Brahmia M E A , Moalic L , et al . A comparative study of meta-heuristic algorithms for WSN deployment problem in indoor environments [C ] // Proceedings of the 2023 IEEE Congress on Evolutionary Computation (CEC) . Piscataway : IEEE Press , 2023 : 1 - 8 .

Hashim F A , Hussien A G . Snake optimizer: a novel meta-heuristic optimization algorithm [J ] . Knowledge-Based Systems , 2022 , 242 : 108320 .

Wang J M , Zhu Z L , Zhang F , et al . An improved salp swarm algorithm for solving node coverage optimization problem in WSN [J ] . Peer-to-Peer Networking and Applications , 2024 , 17 ( 3 ): 1091 - 1102 .

Jonker R , Volgenant A . A shortest augmenting path algorithm for dense and sparse linear assignment problems [J ] . Computing , 1987 , 38 ( 4 ): 325 - 340 .

Li Y C , Han M X , Guo Q L . Modified whale optimization algorithm based on tent chaotic mapping and its application in structural optimization [J ] . KSCE Journal of Civil Engineering , 2020 , 24 ( 12 ): 3703 - 3713 .

Mahdavi S , Rahnamayan S , Deb K . Opposition based learning: a literature review [J ] . Swarm and Evolutionary Computation , 2018 , 39 : 1 - 23 .

Wang Z D , Xie H M , Hu Z D , et al . Node coverage optimization algorithm for wireless sensor networks based on improved grey wolf optimizer [J ] . Journal of Algorithms & Computational Technology , 2019 , 13 : 1748302619889498 .

Turkeshi X , Piroli L , Schiró M . Enhanced entanglement negativity in boundary-driven monitored Fermionic chains [J ] . Physical Review B , 2022 , 106 ( 2 ): 024304 .

Jogam P , Sandhya D , Alok A , et al . A review on CRISPR/Cas-based epigenetic regulation in plants [J ] . International Journal of Biological Macromolecules , 2022 , 219 : 1261 - 1271 .

Kara D , Kimura T , Chen Y T , et al . PhyMask: an adaptive masking paradigm for efficient self-supervised learning in IoT [C ] // Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems . New York : ACM , 2024 : 97 - 111 .

Di Carlo M , Vasile M , Minisci E . Adaptive multi-population inflationary differential evolution [J ] . Soft Computing , 2020 , 24 ( 5 ): 3861 - 3891 .

王丽娟 , 刘姝含 , 王剑 , 等 . 结合精英初始化和 K 近邻的蛇优化算法 [J ] . 计算机应用研究 , 2024 , 41 ( 9 ): 2712 - 2721 .

Wang L J , Liu S H , Wang J , et al . Snake optimization algorithm combining elite initialisation and K -nearest neighbors [J ] . Application Research of Computers , 2024 , 41 ( 9 ): 2712 - 2721 .

Kannan B K , Kramer S N . An augmented Lagrange multiplier based method for mixed integer discrete continuous optimization and its applications to mechanical design [J ] . Journal of Mechanical Design , 1994 , 116 ( 2 ): 405 - 411 .

Hernandez J , Sunny M S H , Sanjuan J , et al . Current designs of robotic arm grippers: a comprehensive systematic review [J ] . Robotics , 2023 , 12 ( 1 ): 50 .

李振 , 冯锋 . 基于Halton序列WOA-GWO算法的WSN覆盖研究 [J ] . 物联网技术 , 2024 , 14 ( 2 ): 43 - 47, 51 .

Li Z , Feng F . Research on WSN coverage based on Halton sequence WOA-GWO algorithm [J ] . Internet of Things Technologies , 2024 , 14 ( 2 ): 43 - 47, 51 .

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