Fuzzy Logic-Based Model for Reducing End-to-End Delay and Enhancing Packet Delivery Ratio in Wireless Sensor Networks

Wireless sensor networks (WSNs) are widely utilized in various applications, including environmental monitoring, industrial automation, and military surveillance. However, their performance is often hindered by high end-to-end delay, which arises from challenges like dynamic network topology, congestion, and suboptimal routing strategies. These issues can lead to delayed data delivery and reduced network responsiveness, especially in densely deployed networks. This paper presents a fuzzy logic-based routing model designed to intelligently select optimal paths by considering residual energy, queue length, and hop count. The fuzzy inference system dynamically balances these inputs to prioritize routes that reduce latency while maintaining network stability and energy efficiency. The proposed model is implemented and tested in MATLAB, with performance evaluated against traditional routing protocols like AODV. Simulation results indicate that the fuzzy model significantly enhances packet delivery ratio and lowers end-to-end delay, especially as node density increases, demonstrating its potential for delay-sensitive WSN applications.