融合思维创新策略改进MOCTCM的隧道WSN分簇路由算法
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TN92

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国家自然科学基金项目(62262038);甘肃省科技计划-中小企业创新基金项目(25CXGA014);甘肃省技术创新引导计划-科技专员专项项目(25CXGA030).


Tunnel WSN clustering routing algorithm integrating thinking innovation strategy to improve MOCTCM
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    摘要:

    延长网络生命周期是隧道无线传感网络亟需解决的核心问题, 而拓扑控制在优化网络生命周期和性能方面具有关键作用. 为提升隧道无线传感器网络在三维场景下的适配性和整体性能, 提出一种融合思维创新策略(TIS)改进MOCTCM的分簇路由算法TIMO. 首先, 构建三维隧道空间模型并推导最优簇头数, 提出基于竞争半径和节点密度的簇头自适应分配机制, 优化布局和负载; 然后, 簇头选举采用TIS改进的MOCTCM算法, 综合考虑剩余能量、簇内距离以及信任度, 路由阶段利用MOCTCM和变异系数法动态权衡总能耗与能耗方差, 优化传输路径; 最后, 通过仿真结果表明, TIMO能够有效均衡网络能耗, 显著延长生命周期.

    Abstract:

    Extending the network lifetime is a critical challenge for tunnel wireless sensor networks, and topology control plays a pivotal role in optimizing both network lifetime and overall performance. To enhance the adaptability and overall performance of tunnel wireless sensor networks (TWSNs) in three-dimensional environments, this paper proposes a TWSN clustering routing algorithm integrating thinking innovation strategy to improve multi-objective competition of tribes and cooperation of members (MOCTCM) (TIMO). First, a 3D tunnel spatial model is constructed to derive the optimal number of cluster heads, and an adaptive cluster head allocation mechanism based on competitive radius and node density is introduced to achieve rational deployment and load balancing. The cluster head election employs a TIS-enhanced MOCTCM algorithm that comprehensively considers residual energy, intra-cluster distance, and node trust. In the routing phase, the MOCTCM combined with the coefficient of variation method is used to dynamically balance total energy consumption and its variance, thus optimizing the transmission path. Simulation results demonstrate that the proposed approach effectively balances network energy consumption and significantly extends network lifetime.

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曹芳,火久元,杨继广.融合思维创新策略改进MOCTCM的隧道WSN分簇路由算法[J].控制与决策,2026,41(7):1945-1957

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  • 收稿日期:2025-10-14
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  • 在线发布日期: 2026-06-23
  • 出版日期: 2026-07-10
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