A Socio-Temporal Cache Prefetching Policy for the Multi-access Edge Computing Architecture

In this paper, we propose a cache prefetching policy for the Multi-access Edge Computing architecture (MEC) that considers the temporal and social behaviors of mobile users. The key point of our policy is to prefetch new contents based on the popularity of their categories and not on the popularity of each content individually. Our goal is to increase the Quality of Experience (QoE) of mobile users by increasing the cache hit ratio. Simulation results show that HASSAN provides a hit ratio up to 65% for a cache size of 16 MB.