An End-to-End Pipeline Perspective on Video Streaming in Best-Effort Networks: A Survey and Tutorial

IF 28 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Leonardo Peroni, Sergey Gorinsky
{"title":"An End-to-End Pipeline Perspective on Video Streaming in Best-Effort Networks: A Survey and Tutorial","authors":"Leonardo Peroni, Sergey Gorinsky","doi":"10.1145/3742472","DOIUrl":null,"url":null,"abstract":"Remaining a dominant force in Internet traffic, video streaming captivates end users, service providers, and researchers. This paper takes a pragmatic approach to reviewing recent advances in the field by focusing on the prevalent streaming paradigm that involves delivering long-form two-dimensional videos over the best-effort Internet with client-side adaptive bitrate (ABR) algorithms and assistance from content delivery networks (CDNs). To enhance accessibility, we supplement the survey with tutorial material. Unlike existing surveys that offer fragmented views, our work provides a holistic perspective on the entire end-to-end streaming pipeline, from video capture by a camera-equipped device to playback by the end user. Our novel perspective covers the ingestion, processing, and distribution stages of the pipeline and addresses key challenges such as video compression, upload, transcoding, ABR algorithms, CDN support, and quality of experience. We review over 200 papers and classify streaming designs by problem-solving methodology, whether based on intuition, theory, or machine learning. The survey further refines these methodology-based categories and characterizes each design by additional traits such as compatible codecs. We connect the reviewed research to real-world applications by discussing the practices of commercial streaming platforms. Finally, the survey highlights prominent current trends and outlines future directions in video streaming.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"38 1","pages":""},"PeriodicalIF":28.0000,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Computing Surveys","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3742472","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

Remaining a dominant force in Internet traffic, video streaming captivates end users, service providers, and researchers. This paper takes a pragmatic approach to reviewing recent advances in the field by focusing on the prevalent streaming paradigm that involves delivering long-form two-dimensional videos over the best-effort Internet with client-side adaptive bitrate (ABR) algorithms and assistance from content delivery networks (CDNs). To enhance accessibility, we supplement the survey with tutorial material. Unlike existing surveys that offer fragmented views, our work provides a holistic perspective on the entire end-to-end streaming pipeline, from video capture by a camera-equipped device to playback by the end user. Our novel perspective covers the ingestion, processing, and distribution stages of the pipeline and addresses key challenges such as video compression, upload, transcoding, ABR algorithms, CDN support, and quality of experience. We review over 200 papers and classify streaming designs by problem-solving methodology, whether based on intuition, theory, or machine learning. The survey further refines these methodology-based categories and characterizes each design by additional traits such as compatible codecs. We connect the reviewed research to real-world applications by discussing the practices of commercial streaming platforms. Finally, the survey highlights prominent current trends and outlines future directions in video streaming.
在最努力的网络中视频流的端到端管道视角:调查和教程
视频流作为互联网流量的主导力量,吸引着终端用户、服务提供商和研究人员。本文采用一种务实的方法,通过关注流行的流媒体范式来回顾该领域的最新进展,流媒体范式涉及使用客户端自适应比特率(ABR)算法和内容交付网络(cdn)的帮助,在尽力的互联网上提供长格式二维视频。为了提高可访问性,我们在调查中补充了教程材料。与现有的调查提供碎片化的视图不同,我们的工作提供了整个端到端流媒体管道的整体视角,从配备摄像头的设备捕获视频到最终用户的播放。我们新颖的视角涵盖了管道的接收、处理和分发阶段,并解决了视频压缩、上传、转码、ABR算法、CDN支持和体验质量等关键挑战。我们回顾了200多篇论文,并根据解决问题的方法对流设计进行了分类,无论是基于直觉、理论还是机器学习。该调查进一步细化了这些基于方法的分类,并通过诸如兼容编解码器等附加特征来描述每种设计。我们通过讨论商业流媒体平台的实践,将审查的研究与现实世界的应用联系起来。最后,该调查强调了视频流媒体的当前趋势和未来发展方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信