Load Aware Traffic Congestion Control Mechanism Using Fuzzy Logic

Recently, vehicular networks (VANETs) have emerged as promising technology for enabling communication between vehicles and infrastructures to improve road safety and driving experience. However, the dynamic nature of VANETs, characterized by rapidly changing traffic conditions and varying network load, poses significant challenges for reliable communication. Congestion control is a critical aspect of VANETs to prevent network saturation, reduce packet loss, and enhance overall system performance. In this context, the application of fuzzy-logic-based approaches offers a flexible and adaptive solution to dynamically adjust the network performance. This research introduced a fuzzy-logic-based congestion control mechanism for VANEts. The approach focused on dynamically adjusting the beacon busy ratio, road segment, and vehicle speed to address the fluctuating traffic condition, thereby mitigating congestion and enhancing vehicular network efficiency. Leveraging fuzzy logic, the proposed system can make route suggestions through the communication between roadside units based on input variables such as beacon busy ratio, road segment, and vehicle speed. On the result and analysis, the performance analysis of the system-based implemented Network Simulator-3 (NS3) and Simulation for Urban Mobility (SUMO) network simulation tool is used. Through simulation, the efficacy of the approach is demonstrated, showing its ability to adapt to evolving traffic dynamics and alleviate congestion on VANETs for enhancing network performance and reliability. The simulation result shows that our proposed system achieves a packet delivery ratio of 95%, throughput of 110 Kbps, and end-to-end delay of 1.93 seconds. This result shows that our scheme is feasible and effective.