高铁场景中基于DASH协议的流媒体自适应云协同传输方法
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:


DASH Protocol-based Adaptive Cloud Collaborative Transmission Method for Streaming Media in High-speed Rail Scenarios
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    高铁逐渐成为流行的出行选择, 高铁途中用户对流媒体服务有着较高的需求. 但是高速移动场景下用户带宽抖动严重、用户的媒体体验难以得到保障. 为此, 本文提出了一种基于DASH协议的跨层流媒体自适应云协同传输优化方法. 首先提出了一个基于DASH协议的跨层流媒体自适应云协同传输架构, 并提出一个高铁环境下用户的QoE模型. 在此基础上构建了基于DASH的跨层流媒体自适应云协同传输的优化模型, 并提出了基于DASH协议的跨层流媒体云协同自适应码率选取算法, 提升用户的媒体体验. 最后仿真实验结果表明, 本文提出的方法能很好地提高高铁用户的媒体体验, 有助于高速移动场景下流媒体优化传输的研究.

    Abstract:

    High-speed rail (HSR) has gradually become a popular travel option, and passengers have high demand for streaming media services during HSR travel. However, in high-speed mobile scenarios, user bandwidth jitter is severe, and user media experience cannot be guaranteed. To this end, a cross-layer optimization method for adaptive cloud collaborative transmission of streaming media, based on DASH protocol, is proposed in this study. Firstly, a cross-layer architecture for adaptive cloud cooperative transmission of streaming media, based on DASH protocol, is proposed, and a QoE model for users in high-speed rail environment is suggested. Next, on this basis, a cross-layer optimization model for adaptive cloud collaborative transmission of streaming media, based on DASH protocol, is constructed, and a cross-layer adaptive bitrate selection algorithm for cloud collaborative transmission of streaming media, based on DASH protocol, is proposed to improve the user’s media experience. Finally, the simulation experiment results show that the method proposed in this study can greatly improve the media experience of HSR passengers, and is helpful for the optimization study of the transmission of streaming media in high-speed mobile scenarios.

    参考文献
    相似文献
    引证文献
引用本文

姜堃.高铁场景中基于DASH协议的流媒体自适应云协同传输方法.计算机系统应用,2024,33(1):263-271

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2023-07-18
  • 最后修改日期:2023-08-24
  • 录用日期:
  • 在线发布日期: 2023-11-28
  • 出版日期: 2023-01-05
文章二维码
您是第位访问者
版权所有:中国科学院软件研究所 京ICP备05046678号-3
地址:北京海淀区中关村南四街4号 中科院软件园区 7号楼305房间,邮政编码:100190
电话:010-62661041 传真: Email:csa (a) iscas.ac.cn
技术支持:北京勤云科技发展有限公司

京公网安备 11040202500063号