面向视频流的MEC缓存转码联合优化研究

李佳; 谢人超; 贾庆民; 黄韬; 刘韵洁; 孙礼

doi:10.11959/j.issn.1000−0801.2018222

您当前的位置：

首页 >

文章列表页 >

面向视频流的MEC缓存转码联合优化研究

研究与开发 | 更新时间：2024-06-05

- 面向视频流的MEC缓存转码联合优化研究
- A survey on joint optimization of MEC caching and transcoding for video streaming
- 电信科学 2018年34卷第8期页码：76-86
- 作者机构：
- 作者简介：
  
  [ "谢德胜（1994−），男，重庆邮电大学移动通信重点实验室硕士生，主要研究方向为移动通信技术、软件定义网络和网络虚拟化。" ]
  [ "柴蓉（1974−），女，重庆邮电大学移动通信重点实验室教授，主要研究方向为移动通信、软件定义网络、物联网、车联网体系架构、无线资源管理及移动性管理技术。" ]
  [ "黄蕾蕾（1995−），女，重庆邮电大学移动通信重点实验室硕士生，主要研究方向为软件定义网络、无线资源管理和网络虚拟化。" ]
  [ "陈前斌（1967−），男，重庆邮电大学副校长、教授、博士生导师，主要研究方向为个人通信、多媒体信息处理与传输和下一代移动通信网络等。" ]
- 基金信息：
  
  中央高校基本科研业务费专项资金资助项目;The Fundamental Research Funds foRthe Central Universities;中央高校基本科研业务费专项资金资助项目；国家自然科学基金资助项目;The Fundamental Research Funds for the Central Universities,The National Natural Science Foundation of China(61501042)
- DOI：10.11959/j.issn.1000−0801.2018222
  中图分类号： TP393
- 网络出版日期：2018-08，
  
  纸质出版日期：2018-08-20
- 稿件说明：
移动端阅览
李佳, 谢人超, 贾庆民, 等. 面向视频流的MEC缓存转码联合优化研究[J]. 电信科学, 2018,34(8):76-86.

Jia LI, Renchao XIE, Qingmin JIA, et al. A survey on joint optimization of MEC caching and transcoding for video streaming[J]. Telecommunications science, 2018, 34(8): 76-86.
李佳, 谢人超, 贾庆民, 等. 面向视频流的MEC缓存转码联合优化研究[J]. 电信科学, 2018,34(8):76-86. DOI： 10.11959/j.issn.1000−0801.2018222.

Jia LI, Renchao XIE, Qingmin JIA, et al. A survey on joint optimization of MEC caching and transcoding for video streaming[J]. Telecommunications science, 2018, 34(8): 76-86. DOI： 10.11959/j.issn.1000−0801.2018222.

摘要

为应对未来移动网络所面临的巨大挑战，业界提出了自适应比特流（adaptive bit rate，ABR）技术和移动边缘计算（mobile edge computing，MEC），旨在为用户提供高体验质量、低时延、高带宽和多样化的服务。联合ABR和MEC来优化视频内容分发，对于提高网络性能和用户体验质量具有重要意义。其中，各项网络资源的联合优化是重要的研究课题。首先对MEC进行了概述，然后基于面向自适应流的MEC缓存转码联合优化问题，对业界已有工作进行了分析和对比，并对未来面临的挑战和研究难点进行了归纳和展望。

Abstract

To deal with the huge challenges in futuremobile networks

the industry has proposed adaptive bit rate(ABR)technology andmobile edge computing(MEC)

aiming to provide users with diverse services of high quality of experience

low latency and high bandwidth.Combining ABR and MEC to optimize the distribution of video content has been quite important for improving network performance and quality of experience.Especially

the joint optimization of network resources has arisen as an essential research topic.An overview of MEC was firstly given

and then the existing work in the industry on the joint optimization problem of MEC caching and transcoding oriented to adaptive streaming was analyzed and compared.Finally

the existing challenges in the future were summarized.

关键词

Keywords

references

Cisco Mobile VNI . Cisco visual networking index:globalmobile data traffic forecast update,2016–2021 white paper [EB/OL ] . 2007 .

STOCKHAMMERt . Dynamic adaptive streaming over HTTP:standards and design principles [C ] // The Second Annual ACM Conference on Multimedia Systems,Feb 23-25,2011,San Jose,CA,USA . New York:ACM Press , 2011 : 133 - 144 .

YIN X Q , JINDAL A , SEKAR V , et al . A control-theoretic approach for dynamic adaptive video streaming over HTTP [C ] // The 2015 ACM Conference on Special Interest Group on Data Communication Pages,August 17-21,2015,London,UK . New York:ACM Press , 2015 : 325 - 338 .

ETSI.Mobile edge computing—a key technology towards 5G [R ] 2015 .

LI Y , FRANGOUDIS P A , HADJADJ-AOUL Y . et al . Amobile edge computing-based architecture for improved adaptive HTTP video delivery [C ] // 2016 IEEE Conference on Standards for Communications and Networking(CSCN),Oct 29-31,2016,Paris,France . Piscataway:IEEE Press , 2016 : 1 - 6 .

WANG C C , LIN Z N , YANG S R , et al . Mobile edge computing-enabled channel-aware video streaming for 4G LTE [C ] // Wireless Communications and Mobile Computing Conference,June 26-30,2017,Valencia,Spain . Piscataway:IEEE Press , 2017 : 564 - 569 .

JIN Y , WEN Y , WESTPHAL C . Optimal transcoding and caching for adaptive streaming inmedia cloud:an analyti cal approach [J ] . IEEE Transactions on Circuits and Systems for Video Technology , 2015 , 25 ( 12 ): 1914 - 1925 .

GAO G , ZHANG W , WEN Y , et al . Towards cost-efficient video transcoding inmedia cloud:insights learned from user viewing patterns [J ] . IEEE Transactions on Multimedia , 2015 , 17 ( 8 ): 1286 - 1296 .

ZHAO H , ZHENG Q , ZHANG W , et al . A segment-based storage and transcoding trade-off strategy formulti-version VoD systems in the cloud [J ] . IEEE Transactions on Multimedia , 2017 , 19 ( 1 ): 149 - 159 .

AHLEHAGH H , DEY S . Adaptive bit rate capable video caching and scheduling [C ] // IEEE WCNC’13,April 7-10,2013,Shanghai,China . Piscataway:IEEE Press , 2013 : 1357 - 1362 .

PEDERSEN H A , DEY S . Enhancingmobile video capacity and quality using rate adaptation,RAN caching and processing [J ] . IEEE/ACM Transactions on Networking , 2016 , 24 ( 2 ): 996 - 1010 .

WANG Z , SUN L , WU C , et al . Joint online transcoding and geo-distributed delivery for dynamic adaptive streaming [C ] // IEEE INFOCOM’14,April 29-May 1,2014,Toronto,Canada . Piscataway:IEEE Press , 2014 : 91 - 99 .

WANG Z , SUN L , WU C , et al . A joint online transcoding and delivery approach for dynamic adaptive streaming [J ] . IEEE Transactions on Multimedia , 2015 , 17 ( 6 ): 867 - 879 .

ZHENG Y , WU D , KE Y , et al . Online cloud transcoding and distribution for crowdsourced live game video streaming [J ] . IEEE Transactions on Circuits and Systems for Video Technology , 2017 , 27 ( 8 ): 1777 - 1789 .

TRAN T X , HAJISAMI A , PANDEY P , et al . Collaborativemobile edge computing in 5G networks:new paradigms,scenarios,and challenges [J ] . IEEE CommunicationsMagazine , 2017 , 55 ( 4 ): 54 - 61 .

TRAN T X , PANDEY P , HAJISAMI A , et al . Collaborativemulti-bitrate video caching and processing inmobile-edge computing networks [C ] // WONS’13,March 18-20,2017,Banff,Canada.[S.l.:s.n . ] , 2017 : 165 - 172 .

XU X , LIU J , TAO X . Mobile edge computing enhanced adaptive bitrate video delivery with joint cache and radio resource allocation [J ] . IEEE Access , 2017 ( 5 ): 16406 - 16415 .

LIANG C , HU S . Dynamic video streaming in caching-enabled wirelessmobile networks [J ] . arXiv:1706.09536 , 2017

王胡成 , 徐晖 , 程志密 , 等 . 5G网络技术研究现状和发展趋势 [J ] . 电信科学 , 2015 , 31 ( 9 ): 149 - 155 .

WANG H C , XU H , CHENG Z M , et al . Current research and development trend of 5G network technologies [J ] . Telecommunications Science , 2015 , 31 ( 9 ): 149 - 155 .

李子姝 , 谢人超 , 孙礼 , 等 . 移动边缘计算综述 [J ] . 电信科学 , 2018 , 34 ( 1 ): 87 - 101 .

LI Z S , XIE R C , SUN L , et al . A survey ofmobile edge computing [J ] . Telecommunications Science , 2018 , 34 ( 1 ): 87 - 101 .

TALEB T , SAMDANIS K , MADA B , et al . Onmulti-access edge computing:a survey of the emerging 5G network edge cloud architecture and orchestration [J ] . IEEE Communication Surveys ＆ Tutorials , 2017 , 19 ( 3 ): 1657 - 1681 .

WANG S , ZHANG X , ZHANG Y , et al . A survey onmobile edge networks:convergence of computing,caching and communications [J ] . IEEE Access , 2017 , 5 ( 3 ): 6757 - 6779 .

TIMMERER C , GRIWODZ C . Dynamic adaptive streaming over HTTP:from content creation to consumption [C ] // Proc.of ACM MM’12,Oct 29-Nov 2,2012,Nara,Japan . New York:ACM Press , 2012 : 1533 - 1534 .

赵希鹏 , 张欣 , 杨大成 , 等 . 基于QoE的无线网络资源调度优化研究 [J ] . 移动通信 , 2014 ( 22 ): 8 - 13 .

ZHAO X P , ZHANG X , YANG D C , et al . Research on optimization of wireless network resource scheduling base on QoE [J ] . Mobile Communications , 2014 ( 22 ): 8 - 13 .

LI C,TONI L , ZOU J , XIONG H , et al . QoE-drivenmobile edge caching placement for adaptive video streaming [J ] . IEEE Transactions on Multimedia , 2017 ( 9 ):1.

HE T Y , ZHAO N , YIN H . Integrated networking,caching and computing for connected vehicles:a deep reinforcement learning approach [J ] . IEEE Transactions on VehiculaRtechnology , 2017 , 99 ( 10 ):1.

GHARAIBEH A , KHREISHAH A , JI B , et al . A provably efficient online collaborative caching algorithm formulticell-coordinated systems [J ] . IEEE Transactions on Mobile Computing , 2016 , 15 ( 8 ): 1863 - 1876 .

WANG W , CAO J , ZHANG W . Edge computing:vision and challenges [J ] . IEEE Internet of Things Journal , 2016 , 3 ( 5 ): 637 - 646 .

项弘禹 , 肖扬文 , 张贤 , 等 . 5G边缘计算和网络切片技术 [J ] . 电信科学 , 2017 , 33 ( 6 ): 54 - 63 .

XIANG H Y , XIAO Y W , ZHANG X , et al . Edge computing and network slicing technology in 5G [J ] . Telecommunications Science , 2017 , 33 ( 6 ): 54 - 63 .

GPPP E B . QoE-orientedmobile edge servicemanagement leveraging SDNand NFV [J ] . Mobile Information Systems , 2017 ( 1 ).

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于5G MEC的水泥智慧工厂解决方案研究与验证

5G智慧校园业务场景中MEC分流方案研究

5G行业无线专网技术与业务需求模型

基于MEC的车联网技术研究及应用

C-V2X车联网关键技术与方案概述