Adaptive Swarm Intelligence Routing for Energy-Efficient IoT Communications

The rapid growth of the Internet of Things (IoT) has led to the widespread deployment of large-scale sensor networks that operate under strict energy limitations. Ensuring dependable communication while maximizing network lifetime requires efficient routing strategies. However, traditional routing protocols often fail to adapt to dynamic network environments, resulting in inefficient energy utilization. To address this issue, this study introduces an adaptive routing protocol based on swarm intelligence, leveraging bio-inspired optimization techniques to select energy-efficient paths dynamically. The proposed approach considers multiple factors such as residual energy, transmission distance, link reliability, and delay to make optimal routing decisions. Simulation outcomes demonstrate significant enhancements in energy efficiency, packet delivery performance, and overall network lifespan compared to conventional methods. This intelligent and scalable solution shows strong potential for improving the performance of next-generation IoT systems.