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arXiv · 2309.01944

Duration-adaptive Video Highlight Pre-caching for Vehicular Communication Network

Liang Xu·Deshi Li·Kaitao Meng·Mingliu Liu·Shuya Zhu
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Abstract

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.

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Liang Xu, Deshi Li, Kaitao Meng, Mingliu Liu, Shuya Zhu. 2023-09-05. Duration-adaptive Video Highlight Pre-caching for Vehicular Communication Network. https://arxiv.org/abs/2309.01944

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