Enhancing Real-Time IoT Applications through Edge Computing, SDN, and IoT Integration

This research investigates the incorporation of Edge Computing within the realm of in-vehicle infotainment systems in connected vehicles. Our objective is to examine the technical challenges and opportunities associated with this integration, particularly in enhancing the user experience. The study highlights the significance of the Internet of Vehicles (IoV), evaluating its potential advantages regarding safety, convenience, and overall passenger experience. Furthermore, we propose an Edge Computing architecture that utilizes Software Defined Networking (SDN) to mitigate traffic congestion in IoV networks. Our methodology introduces two dynamic routing strategies aimed at optimizing network traffic by shifting computation and data processing to the network edge. This strategy reduces the load on the core network, thereby facilitating real-time decision-making and minimizing latency. The proposed architecture is implemented and assessed within the Omnet++ simulation environment, employing performance metrics to evaluate its effectiveness in enhancing traffic management and the performance of IoV systems. The results from our experiments confirm the feasibility of our approach, demonstrating significant improvements in the optimization of IoV networks.