In the Internet of Things (IoT) networks, the Routing Protocol forLow-power and Lossy Networks (RPL) is a widely adopted standard due toits efficiency in managing resource-constrained and energy-limited nodes.However, persistent challenges such as high energy consumption, unstablelinks, and suboptimal routing continue to hinder network performance,affecting both the longevity of the network and the reliability of datatransmission. This paper proposes an enhanced RPL routing mechanismby integrating the Tabu Search optimization algorithm to address theseissues. The proposed approach focuses on optimizing the parent and childselection process in the RPL protocol, leveraging a composite cost func-tion that incorporates key parameters including Residual Energy, Trans-mission Energy, Distance to Sink, Hop Count, Expected TransmissionCount (ETX), and Link Stability Rate. Through extensive simulations,we demonstrate that our method significantly improves link stability, re-duces energy consumption, and enhances the packet delivery ratio, leadingto a more efficient and longer-lasting IoT network. The findings suggestthat Tabu Search can effectively balance the trade-offs inherent in IoTrouting, providing a practical solution for improving the overall perfor-mance of RPL-based networks.

翻译：在物联网网络中，低功耗有损网络路由协议因其在资源受限和能量有限节点管理方面的效率而被广泛采用。然而，高能耗、链路不稳定和次优路由等持续存在的挑战仍然阻碍着网络性能，既影响网络寿命也影响数据传输的可靠性。本文通过集成禁忌搜索优化算法提出一种增强型RPL路由机制以解决这些问题。所提方法聚焦于优化RPL协议中的父节点与子节点选择过程，采用融合关键参数的复合成本函数，包括剩余能量、传输能量、到汇聚节点的距离、跳数、期望传输计数以及链路稳定率。通过大量仿真实验，我们证明该方法能显著提升链路稳定性、降低能耗并提高数据包投递率，从而构建更高效且寿命更长的物联网网络。研究结果表明，禁忌搜索能够有效平衡物联网路由中固有的权衡关系，为提升基于RPL网络的整体性能提供了实用解决方案。