MOBILITY AND CLOUD MANAGEMENT IN WIRELESS HETEROGENEOUS 5G NETWORKS
VANETs, Fog, Edge, 5G, Mobilty, Ultra-dense networks
Mobility management is a key area to ensure connectivity and the continuity of the services consumed by mobile users. This dissertation analyzes how the next generation of 5G ultra-dense networks will pave the way for the distribution of video in vehicular networks (VANETs), which will be composed of a heterogeneous ultra-dense infrastructure, joining existing wireless communication technologies to obtain greater spectral efficiency. A handover algorithm, called HoVe, is the mais contribution of this work. HoVe is an algorithm based on multiple criteria for video distribution on ultra-dense 5G VANETs. The simulation results show HoVe’s efficiency in providing videos with 19 % higher quality than state-of-the-art algorithms, improving the package delivery rate by at least 30%. This work studies a particular case of VANETs that benefits from computing at the edge of the network, the case of Autonomous Connected Vehicles, or CAVs. Edge and mist computing are emerging solutions for remote data processing for autonomous vehicles, offering higher computational power, as well as the low latency required by autonomous driving. This work also proposes the MOSAIC algorithm for service migration and resource management for communication between layers and between layers in edge and fog computing. Simulation results show the efficiency of the proposed algorithm in terms of latency, migration failures, and network throughput.