  Mobile Edge Caching is a promising technique to enhance the content delivery
quality and reduce the backhaul link congestion, by storing popular content at
the network edge or mobile devices (e.g. base stations and smartphones) that
are proximate to content requesters. In this work, we study a novel mobile edge
caching framework, which enables mobile devices to cache and share popular
contents with each other via device-to-device (D2D) links. We are interested in
the following incentive problem of mobile device users: whether and which users
are willing to cache and share what contents, taking the user mobility and
cost/reward into consideration. The problem is challenging in a large-scale
network with a large number of users. We introduce the evolutionary game
theory, an effective tool for analyzing large-scale dynamic systems, to analyze
the mobile users' content caching and sharing strategies. Specifically, we
first derive the users' best caching and sharing strategies, and then analyze
how these best strategies change dynamically over time, based on which we
further characterize the system equilibrium systematically. Simulation results
show that the proposed caching scheme outperforms the existing schemes in terms
of the total transmission cost and the cellular load. In particular, in our
simulation, the total transmission cost can be reduced by 42.5%-55.2% and the
cellular load can be reduced by 21.5%-56.4%.
