Rajan Sherine Jenny, Narayanaswamy Sugirtham, Balashanmugam Thiyaneswaran, Sengottaiyan Kumarganesh, Selvaraj Anthoniraj, Majumder Pratham, Al-Rasheed Amal, Getahun Masresha, Soufiene Ben Othman
Department of ECE, Dr.Mahalingam College of Engineering and Technology, Coimbatore, Tamil Nadu, India.
Department of ECE, Sona College of Technology, Salem, Tamil Nadu, India.
Sci Rep. 2025 Apr 6;15(1):11785. doi: 10.1038/s41598-025-96365-0.
Improving road safety and easing congestion require effective real-time traffic data analysis and management. A crucial part of intelligent transportation systems, vehicular ad hoc networks (VANETs) deal with issues like inconsistent data from erratic vehicle movements and frequent topology changes. In order to develop a responsive and adaptable network management architecture for VANETs, this study makes use of Software-Defined Networking (SDN). SDN optimizes traffic flow, boosts routing efficiency, and improves Quality of Service (QoS) by separating the control and data planes. Traffic analysis and network performance are greatly improved when SDN is combined with priority algorithms and the Zigbee protocol. The effectiveness of this strategy in a controlled setting is shown by simulations conducted with COOJA software. Web digitization tools are also used to guarantee the accuracy of the data. Improved QoS, better traffic flow management, and scalable solutions for dynamic vehicular networks are some of the main results.
改善道路安全和缓解拥堵需要有效的实时交通数据分析与管理。车载自组织网络（VANETs）作为智能交通系统的关键部分，要应对诸如车辆不稳定运动导致的数据不一致以及频繁的拓扑变化等问题。为了开发一种适用于VANETs的响应式且适应性强的网络管理架构，本研究采用了软件定义网络（SDN）。SDN通过分离控制平面和数据平面来优化交通流、提高路由效率并改善服务质量（QoS）。当SDN与优先级算法和Zigbee协议相结合时，交通分析和网络性能会得到极大提升。使用COOJA软件进行的模拟展示了该策略在受控环境中的有效性。还使用了网络数字化工具来确保数据的准确性。主要成果包括提高了QoS、改善了交通流管理以及为动态车载网络提供了可扩展的解决方案。
