DYNAMIC UAV-ENABLED MOBILE EDGE COMPUTING SERVICE MIGRATION FOR BEYOND 5G NETWORKS
Service migration; B5G; massive-extended reality; Optimization; MEC
The sixth-generation (6G) technology of mobile networks will establish new standards to fulfill unreachable performance requirements by fifth-generation (5G) mobile networks. This is due to the high requirements for a more intelligent network, ultra-lower latency, extreme network communication speed, and supporting a massive number of connected applications. In this context, Mobile Edge Computing (MEC) and service migration strategies have shown promising results in improving the user experience, meeting requirements of beyond 5G networks (B5G), and optimizing infrastructure resources. In addition, Unmanned Aerial Vehicles (UAVs) are a promising solution to provide cloud and edge services in collaboration with MEC scenarios. However, most strategies have ignored resources available on users' devices and contextual information. Motivated by the use of massive-extended reality (XR) and virtual reality (VR) applications in B5G networks, this thesis proposal presents a video service migration strategy based on contextual information and evaluates the influence of user mobility on migration strategies, called Dynamic Video Service Migration (DVSM). Simulation results highlight $74\%$ higher performance of the DVSM compared to state-of-the-art algorithms and a performance equivalent to the optimal solution when the collection and analysis of context information (remaining device's energy, user's location, network conditions, etc) are carried out correctly.