An Integrated Energy-Efficient and Qos-Oriented Model for Industrial Wireless Sensor Network Optimization

Abstract

This paper proposes an enhanced network architecture for Industrial Wireless Sensor Networks (IWSNs) aimed at improving Quality of Service (QoS) through optimized clustering and energy-efficient routing. The proposed model integrates Grey Wolf Optimization (GWO) for intelligent cluster head selection with the Hierarchical Threshold-sensitive Energy Efficient Network (H-TEEN) protocol to enhance data transmission reliability. GWO dynamically selects optimal cluster heads based on residual energy and node proximity, ensuring balanced energy consumption and prolonged network lifetime. The H-TEEN protocol is adapted to manage heterogeneous nodes and hierarchical communication, reducing latency and transmission overhead. This hybrid approach ensures efficient energy usage, enhances fault tolerance, and meets strict industrial QoS requirements. MATLAB-based simulations demonstrate improved performance over conventional protocols such as LEACH, PSO, and ACO in terms of energy consumption, packet delivery ratio, and network stability. The proposed architecture offers a robust solution for real-time monitoring and control in industrial automation environments.