Joint Video Caching and User Association With Mobile Edge Computing

Abstract

The rapid increasing of mobile video traffic has put heavy burden on mobile networks. Mobile edge computing (MEC) has become a promising paradigm to provide caching, computing and context awareness ability within the radio access network (RAN) so as to cache popular videos and provide multi-bitrate video streaming to users nearby. In this paper, we propose joint user association and cache strategy to maximize the system revenue by combining caching, transcoding and adaptive bitrate streaming (ABR) technology. The backhaul bandwidth saved by caching and transcoding is regarded as the system gains and the system resources (eg., cache resources, transcoding resources) consumed are as cost so as to use limited system resources to bring greater benefits to the system. Finally, the optimization problem is solved by using many-to-many matching algorithm. The experimental results show that the proposed cache scheme has a better performance than other cache schemes.