Mobility-Aware Edge Caching For Connected Cars

Content caching on the edge of 5G networks is an emerging and critical feature to support the thirst for content of future connected cars. Yet, the compactization of 5G cells, the finite edge storage capacity and the need for content availability while driving motivate the need to develop smart edge caching strategies adapted to the mobility characteristics of connected cars. In this paper, we propose a Mobility-Aware Probabilistic (MAP) scheme, which optimally caches content at edge nodes where connected vehicles mostly require it. Unlike blind popularity decisions, the probabilistic caching used by MAP considers vehicular trajectory predictions as well as content service time by edge nodes. We evaluate our approach on realistic mobility datasets and against popularity-based edge approaches. Our MAP edge caching scheme provides up to 40% enhanced content availability, 70% increased cache throughput, and 40% reduced backhaul overhead compared to popularity-based strategies.