  Video traffic in vehicular communication networks (VCNs) faces exponential
growth. However, different segments of most videos reveal various
attractiveness for viewers, and the pre-caching decision is greatly affected by
the dynamic service duration that edge nodes can provide services for mobile
vehicles driving along a road. In this paper, we propose an efficient video
highlight pre-caching scheme in the vehicular communication network, adapting
to the service duration. Specifically, a highlight entropy model is devised
with the consideration of the segments' popularity and continuity between
segments within a period of time, based on which, an optimization problem of
video highlight pre-caching is formulated. As this problem is non-convex and
lacks a closed-form expression of the objective function, we decouple multiple
variables by deriving candidate highlight segmentations of videos through
wavelet transform, which can significantly reduce the complexity of highlight
pre-caching. Then the problem is solved iteratively by a highlight-direction
trimming algorithm, which is proven to be locally optimal. Simulation results
based on real-world video datasets demonstrate significant improvement in
highlight entropy and jitter compared to benchmark schemes.
