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arXiv 2408.06702cs.NI
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利用禁忌搜索优化RPL路由以提高物联网网络中的链路稳定性与能耗

Optimizing RPL Routing Using Tabu Search to Improve Link Stability and Energy Consumption in IoT Networks

University of Verona(维罗纳大学);University of Extremadura(埃斯特雷马杜拉大学);Islamic Azad University Ardabil Branch(伊斯兰阿扎德大学阿尔达比勒分校)

Mehran Tarif, Mohammadhossein Homaei, Abbas Mirzaei, Babak Nouri-Moghaddam

AI总结:

本文提出一种结合禁忌搜索算法的改进RPL路由机制,通过优化父节点和子节点选择过程,提升链路稳定性、降低能耗并提高数据包交付率。

摘要:

在物联网网络中,低功耗和丢包率网络路由协议(RPL)因其在管理受限资源和能量限制节点方面的效率而被广泛采用。然而,持续存在的挑战如高能耗、不稳定链路和次优路由仍然阻碍网络性能,影响网络寿命和数据传输可靠性。本文提出了一种改进的RPL路由机制,通过整合禁忌搜索(TS)优化算法来解决这些问题。所提出的方法聚焦于优化RPL协议中的父节点和子节点选择过程,利用一个综合成本函数,该函数结合了残余能量、传输能量、到汇点的距离、跳数(HC)、预期传输次数(ETX)和链路稳定性率(LSR)。通过广泛的模拟,我们证明了我们的方法显著提高了链路稳定性,减少了能耗,并提高了数据包交付比,从而实现更高效且更持久的物联网网络。研究结果表明,TS能够有效平衡物联网路由中固有的权衡,为改进基于RPL的网络整体性能提供了实用的解决方案。

英文摘要:

In the Internet of Things (IoT) networks, the Routing Protocol for Low-power and Lossy Networks (RPL) is a widely adopted standard due to its efficiency in managing resource-constrained and energy-limited nodes. However, persistent challenges such as high energy consumption, unstable links, and suboptimal routing continue to hinder network performance, affecting both the longevity of the network and the reliability of data transmission. This paper proposes an enhanced RPL routing mechanism by integrating the Tabu Search (TS) optimization algorithm to address these issues. The proposed approach focuses on optimizing the parent and child selection process in the RPL protocol, leveraging a composite cost function that incorporates critical parameters, including Residual Energy, Transmission Energy, Distance to Sink, Hop Count(HC), Expected Transmission Count (ETX), and Link Stability Rate(LSR). Through extensive simulations, we demonstrate that our method significantly improves link stability, reduces energy consumption, and enhances the packet delivery ratio, leading to a more efficient and longer-lasting IoT network. The findings suggest that TS can effectively balance the trade-offs inherent in IoT routing, providing a practical solution for improving the overall performance of RPL-based networks.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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