An Innovative Intelligent-Inspired Optimization Scheme for Energy-Efficient Cluster Routing in the Consumer Industrial Internet of Things

In the context of the rapidly evolving Consumer Consumer Industrial Wireless Sensor Networks (IWSNs), the expansion of the Consumer Industrial Internet of Things (IoT) has intensified the need for energy-efficient routing protocols capable of addressing the energy limitations of sensor nodes. This paper introduces a novel routing protocol, the Chaotic Lévy Random Walk Carnivorous Plant Algorithm for Cluster-based Routing (CLRWCPA-CR), specifically designed to enhance energy efficiency and prolong the operational lifetime of IWSNs. A novel and efficient clustering routing model for IWSNs is proposed, considering multiple key factors during its design, including intra-cluster distance, base station distance, cluster head energy, and cluster member energy. The CLRWCPA-CR protocol integrates chaotic strategies, Lévy flights, random walk techniques, and carnivorous plant strategies to optimize cluster-based routing, thereby accelerating convergence and expanding the solution space. Extensive experimental evaluations, conducted under realistic industrial scenarios, demonstrate that CLRWCPA-CR significantly outperforms traditional protocols such as LEACH-C and heuristic methods like GSHFA-HCP and EEM-CRP. It achieves at least 44.3% throughput improvement and extends at least 68.98% network lifetime. The innovative design of the CLRWCPA-CR protocol not only enhances clustering and routing efficiency, but also demonstrates practical value for real-world IoT deployments by improving scalability, reducing energy costs, and supporting long-term, reliable industrial operations.