Optimizing IoT Communication: Context-Aware Energy and Congestion-Aware Cluster Routing
International journal of intelligent engineering and systems · 2025
In the Internet of Things (IoT), ensuring context awareness, energy efficiency, and load balancing is critical for achieving reliable and scalable communication in dynamic, resource-constrained environments.Routing protocols form the backbone of efficient path establishment and seamless data transmission among networked devices.However, limited battery capacity, high node mobility, and frequent link disruptions severely challenge traditional routing approaches.To address these issues, this paper proposes an adaptive, energy-aware, context-driven routing framework based on the Lightweight On-Demand Ad hoc Distance-vector routing protocol-Next Generation (LOADng), enhanced with a modified Dingo Optimization Algorithm.The proposed system introduces a novel context-aware clustering mechanism that intelligently selects cluster heads (CHs) and relay nodes (RLYs), significantly reducing routing overhead and enhancing scalability.The resulting protocol DOACAR is evaluated using the ns-3 network simulator.Comparative analyses with existing protocols, including LOADng-IoT-Mob and EMA-RPL, demonstrate that DOACAR achieves a 32% reduction in average energy consumption, a 28% decrease in end-to-end delay, and a 35% improvement in packet delivery ratio.Furthermore, the network lifetime is extended by up to 41%, highlighting DOACAR's superior energy efficiency, reliability, and adaptability.These results affirm the effectiveness of the proposed system in optimizing resource utilization, extending network longevity, and offering a robust, scalable solution for next-generation IoT deployments.