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

The Routing Protocol for Low-power and Lossy Networks (RPL) is widely used in Internet of Things (IoT) systems, where devices usually have very limited resources. However, RPL still faces several problems, such as high energy usage, unstable links, and inefficient routing decisions, which reduce the overall network performance and lifetime. In this work, we introduce TABURPL, an improved routing method that applies Tabu Search (TS) to optimize the parent selection process. The method uses a combined cost function that considers Residual Energy, Transmission Energy, Distance to the Sink, Hop Count, Expected Transmission Count (ETX), and Link Stability Rate (LSR). Simulation results show that TABURPL improves link stability, lowers energy consumption, and increases the packet delivery ratio compared with standard RPL and other existing approaches. These results indicate that Tabu Search can handle the complex trade-offs in IoT routing and can provide a more reliable solution for extending the network lifetime.