Vehicular Ad Hoc Networks (VANETs) play a critical role in ensuring safety and welfare applications for drivers and passengers amidst the escalating vehicular population in urban environments. The efficient functioning of VANETs hinges on addressing the challenge of load balancing among Road Side Units (RSUs). This paper introduces a groundbreaking approach aimed at enhancing real-time data transmission services within VANETs. The key contribution lies in the development of a multicast routing algorithm utilizing a geo-targeting protocol, facilitating simultaneous delivery of source data packets to multiple destinations. This innovative strategy aims to alleviate RSU congestion, thereby significantly enhancing the quality of real-time data transmission services. Moreover, this study presents advancements in the Statistical Match and Queuing algorithm, refining it over time to substantially mitigate network congestion and redundancy. Additionally, a Multi-Protocol Label Switching based algorithm is implemented to elevate service quality parameters, including end-to-end latency, packet loss, and overall network efficiency within in-vehicle networks. Importantly, this approach remains adaptable across various Layer two technologies, ensuring compatibility and scalability. Simulation results validate the efficacy of the proposed methodology, showcasing its superiority over existing methods. The findings underscore the innovative algorithms’ prowess in addressing load balancing challenges across diverse scenarios, affirming their potential to significantly enhance VANET service quality.

在城市环境中车辆数量不断增加的情况下，车辆自组织网络 (VANET) 在确保驾驶员和乘客的安全和福利应用方面发挥着关键作用。VANET 的高效运行取决于解决路边单元 (RSU) 之间负载平衡的挑战。本文介绍了一种旨在增强 VANET 内实时数据传输服务的突破性方法。关键贡献在于开发了利用地理定位协议的多播路由算法，有助于将源数据包同时传送到多个目的地。这一创新策略旨在缓解RSU拥塞，从而显着提高实时数据传输服务的质量。此外，这项研究还展示了统计匹配和排队算法的进步，并随着时间的推移对其进行改进，以显着减轻网络拥塞和冗余。此外，还实施了基于多协议标签交换的算法，以提高服务质量参数，包括车载网络内的端到端延迟、数据包丢失和整体网络效率。重要的是，这种方法仍然适用于各种第二层技术，确保兼容性和可扩展性。仿真结果验证了所提出方法的有效性，显示了其相对于现有方法的优越性。研究结果强调了创新算法在解决不同场景的负载平衡挑战方面的能力，肯定了它们显着提高 VANET 服务质量的潜力。