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

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.