## 1 Introduction
This advancement allows vehicles to offload computationally heavy tasks to MEC servers with low latency. In the context of vehicular networks, MEC entails placing small-scale data centers or servers in important areas, such as base stations or RSUs, to execute functions that would normally need connection with a distant central cloud. This proximity dramatically reduces end-to-end latency, which is critical for real-time applications, including self-driving cars, collision avoidance, and high-definition mapping [10]. However, the complicated network environment and vehicles' intrinsic mobility pose issues typical offloading solutions frequently fail to meet. Fog computing extends cloud computing to the network edge, distributing data processing instead of centralization. Fog computing in vehicular networks uses roadside equipment, traffic signals, and automobiles to process data closer to where it is created. This distributed strategy minimizes latency and boosts network resiliency [8]. Fog computing aids traffic management, smart parking, emergency response, and environmental monitoring in automotive networks. It provides instant insights and reactions for time-sensitive applications by processing data locally. Fog computing's distributed nature makes vehicular networks more scalable, allowing them to handle the large data flow from linked vehicles and smart infrastructure. It lessens the load on centralized data centers, improving network efficiency and sustainability [11]. SDN is a networking framework that isolates the control and data planes, allowing for programmable administration. SDN allows VANETs to be more adaptable and dynamic, which is necessary for controlling vehicular networks' mobility. It allows network administrators to apply policies, optimize traffic flow, and improve security through a centralized controller monitoring the entire network. Furthermore, SDN centralizes control to optimize routing patterns and manage network resources, decreasing congestion and improving network performance. SDN's programmability rapidly adapts to changing network conditions, which is essential for dependable communication in dynamic vehicle contexts. This adaptability helps advanced applications, including real-time traffic management, emergency vehicle prioritization, and adaptive streaming [12]. Microservice in VANET is a promising software design and implementation approach that offers many benefits. Microservices facilitate dividing intricate applications into more manageable, autonomous, and independently implemented and expanded parts. It provides higher flexibility, modularity, and scalability in designing and implementing VANET applications [13]. Microservices can also improve fault tolerance, reliability, performance, and efficiency. Additionally, microservices enable greater flexibility and modularity in designing and implementing VANET applications, allowing for easier customization to meet the specific needs of different use cases and environments. As VANET systems become more complex and diverse, microservices will become increasingly important for successfully deploying and operating VANET applications. Microservices offer a promising approach to developing VANET systems that can improve reliability, efficiency, and flexibility [14]. The handover and migration processes are critical operations in VANET that enable seamless communication between network infrastructure. The handover process is challenging due to high vehicle mobility, network topology changes, and maintaining service continuity during handovers. Effective handover and migration mechanisms are essential for reducing service disruption and improving the reliability and performance of VANET applications [15]. The migration process is also important for integrating different network technologies and architectures, enabling efficient resource utilization, and reducing service disruption during handovers [16].