Joint optimization of transmission and edge offloading for energy-aware point cloud video streaming

LIU Wei; ZHU Yule; FU Chen; WANG Xi

doi:10.11959/j.issn.1000-436x.2024098

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Joint optimization of transmission and edge offloading for energy-aware point cloud video streaming

Papers | 更新时间：2024-06-24

- Joint optimization of transmission and edge offloading for energy-aware point cloud video streaming
- Journal on Communications Vol. 45, Issue 5, Pages: 80-89(2024)
- 作者机构：
  
  华中科技大学电子信息与通信学院，湖北武汉 430074
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61977064);The National Key Research and Development Program of China(2021YFC3340802)
- DOI：10.11959/j.issn.1000-436x.2024098
  CLC： TN919.82
- Received：05 February 2024，
  
  Revised：2024-04-19，
  
  Published：30 May 2024
- 稿件说明：
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刘威,朱雨乐,付晨等.能量感知的点云视频流传输与边缘卸载联合优化[J].通信学报,2024,45(05):80-89.

LIU Wei,ZHU Yule,FU Chen,et al.Joint optimization of transmission and edge offloading for energy-aware point cloud video streaming[J].Journal on Communications,2024,45(05):80-89.
刘威,朱雨乐,付晨等.能量感知的点云视频流传输与边缘卸载联合优化[J].通信学报,2024,45(05):80-89. DOI： 10.11959/j.issn.1000-436x.2024098.

LIU Wei,ZHU Yule,FU Chen,et al.Joint optimization of transmission and edge offloading for energy-aware point cloud video streaming[J].Journal on Communications,2024,45(05):80-89. DOI： 10.11959/j.issn.1000-436x.2024098.

摘要

针对点云视频流媒体传输需要调度各类计算和传输资源，而现有工作较少考虑终端显示设备的计算任务带来的能耗问题，提出了一种移动边缘计算辅助的点云视频流传输方案，根据接入带宽和点云视频内容将部分计算任务从终端卸载到边缘完成。该方案建立了一个联合优化模型，在网络资源、终端和边缘算力资源的约束下，最大化用户观看体验收益并最小化终端设备能耗。实验表明，相比于对比方案，所提方案在不同条件下均可提升用户观看质量并降低终端设备能耗。

Abstract

The transmission of point cloud video streaming requires the scheduling of various computing and transmission resources. Existing research rarely considers the energy consumption issues caused by the computing tasks of terminal display devices. To solve this problem

a point cloud video streaming transmission scheme assisted by mobile edge computing (MEC) was proposed

which offloaded part of computing tasks to the MEC server based on the access bandwidth and point cloud video content. A joint optimization model was established in this scheme to maximize the quality of user’s viewing experience and minimize the energy consumption of terminal device under the constraints of network resources

terminal and edge computing resources. Experimental results show that the proposed scheme can improve the viewing quality of users and reduce the energy consumption of terminal equipment compared with the contrast scheme under different conditions.

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references

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