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基于深度学习的缓存优化,用于车辆边缘计算中的VR 360°视频

Shahbaz Khan1, Jinling Zhang2, Kamlesh Kumar Soothar1

  • 1School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China.

Scientific reports
|November 25, 2025
PubMed
概括

DeepEdge360优化了使用深度学习在车辆边缘计算 (VEC) 中的虚拟现实 (VR) 360°视频缓存. 它显著提高了缓存命中率,并减少了在移动车辆中无VR流媒体的延迟.

关键词:
360°视频缓存可以使用.深度强化学习学习 (deep reinforcement learning) 是一种深度强化学习的方法.车辆网络 车辆网络视窗预测的预测

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