Trajectory-Aware Framework for Dynamic MEC Server Selection in 5G Networks

With each new iteration of mobile wireless networks, demands for low latency and real-time processing continue to grow. Traditional cloud-based processing suffers from latency and bandwidth issues, hindering real-time applications. To address this, we propose an architecture that distributes computation to edge servers in order to reduce latency and improve the user experience. Using the OMNeT++ platform with Simu5G and INET libraries, we simulate a detailed 5G network with MEC integration. Central to our architecture is the MEC Orchestrator, which manages edge computing resources and interacts with the MEC Hosts which are small edge-located servers that process data and deliver services closer to the user, minimizing latency and improving the user experience. We then simulate the dynamic interactions between a mobile user's User Equipment (UE) and the MEC infrastructure. To further enhance the efficiency of our proposed architecture, we propose to integrate an algorithm that can predict the UE's future location. This algorithm will enable optimal MEC Host selection for user tasks, ensuring data processing occurs closest to the user's predicted future location.