  Edge caching is being explored as a promising technology to alleviate the
network burden of cellular networks by separating the computing functionalities
away from cellular base stations. However, the service capability of existing
caching scheme is limited by fixed edge infrastructure when facing the
uncertainties of users' requests and locations. The vehicular caching, which
uses the moving vehicles as cache carriers, is regard as an efficient method to
solve the problem above. This paper studies the effectiveness of vehicular
caching scheme in content centric networks by developing optimization model
towards the minimization of network energy consumption. Particularly, we model
the interactions between caching vehicles and mobile users as a 2-D Markov
process, in order to characterize the network availability of mobile users.
Based on the developed model, we propose an online vehicular caching design by
optimizing network energy efficiency. Specifically, the problem of caching
decision making is firstly formulated as a fractional optimization model,
towards the optimal energy efficiency. Using nonlinear fractional programming
technology and Lyapunov optimization theory, we derive the theoretical solution
for the optimization model. An online caching algorithm to enable the optimal
vehicular caching is developed based on the solution. Finally, extensive
simulations are conducted to examine the performance of our proposal. By
comparison, our online caching scheme outperforms the existing scheme in terms
of energy efficiency, hit ratio, cache utilization, and system gain.
