A Deep Reinforcement Learning Approach for Point Cloud Video Transmissions

Hai, Lin; Bo, Zhang; Cao, Yangjie; Liu, Zhi; Chen, Xianfu

doi:10.1109/vtc2021-fall52928.2021.9625496

Cited by 4 publications

(1 citation statement)

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“…Edge device cache task allocation refers to the allocation of video content delivery tasks to different cache devices according to certain strategies in the edge computing environment to optimize the transmission quality and user experience of streaming video [16]. The optimization control method for streaming video transmission based on deep reinforcement learning can effectively solve the problem of edge device caching task allocation [17].…”

Section: A Edge Device Cache Task Allocationmentioning

confidence: 99%

A Deep Reinforcement Learning-Based Optimal Transmission Control Method for Streaming Videos

Yang,

Xiao

2024

IEEE Access

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Time delay and image quality degradation are main challenges faced by streaming video transmission. How to make adaptive planning for transmission schemes according to dynamic change of transmission environment, always remains a technical concern. As a consequence, this paper proposes a deep reinforcement learning-based optimal transmission control method for streaming videos. Firstly, edge buffer task allocation is combined with quality of experience (QoE)-oriented deep reinforcement learning algorithm, in order to develop a resource allocation method for streaming videos. Secondly, an actively coordinated streaming data streaming transmission mechanism is established to construct a specific optimal transmission control method that satisfies environment requirement. Finally, a set of experiments are conducted to verify effectiveness and performance on public video transmission datasets. And the proposal is compared with several traditional transmission methods. The experiments show that the proposal in this work can effectively reduce delay and startup time and improve the QoE. This shows that the proposal is able to bring better stability and transmission quality.

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Section: A Edge Device Cache Task Allocationmentioning

confidence: 99%