An End-to-End Pipeline Perspective on Video Streaming in Best-Effort Networks: A Survey and Tutorial
March 08, 2024 ยท The Cartographer ยท ๐ ACM Computing Surveys
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"Title-pattern auto-detect: An End-to-End Pipeline Perspective on Video Streaming in Best-Effort Networks: A Survey and Tutorial"
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Authors
Leonardo Peroni, Sergey Gorinsky
arXiv ID
2403.05192
Category
cs.NI: Networking & Internet
Cross-listed
cs.MM
Citations
13
Venue
ACM Computing Surveys
Last Checked
3 days ago
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 their problem-solving methodology, whether based on intuition (simple heuristics), theory (formal optimization), or machine learning (generalizable data patterns). The survey further refines these methodology-based categories and characterizes each design by additional traits such as compatible codecs and use of super resolution. 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.
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