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Confused, timid, and unstable: picking a video streaming rate is hard

Published: 14 November 2012 Publication History

Abstract

Today's commercial video streaming services use dynamic rate selection to provide a high-quality user experience. Most services host content on standard HTTP servers in CDNs, so rate selection must occur at the client. We measure three popular video streaming services -- Hulu, Netflix, and Vudu -- and find that accurate client-side bandwidth estimation above the HTTP layer is hard. As a result, rate selection based on inaccurate estimates can trigger a feedback loop, leading to undesirably variable and low-quality video. We call this phenomenon the "downward spiral effect", and we measure it on all three services, present insights into its root causes, and validate initial solutions to prevent it.

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Summary Review Documentation for "Confused, Timid, and Unstable: Picking a Video Streaming Rate is Hard", Authors: T. Huang, N. Handigol, B. Heller, N. McKeown, R. Johari

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      cover image ACM Conferences
      IMC '12: Proceedings of the 2012 Internet Measurement Conference
      November 2012
      572 pages
      ISBN:9781450317054
      DOI:10.1145/2398776
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 14 November 2012

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      Author Tags

      1. http-based video streaming
      2. video rate adaptation

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      IMC '12: Internet Measurement Conference
      November 14 - 16, 2012
      Massachusetts, Boston, USA

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      • (2025)Chasing Common Knowledge: Joint Large Model Selection and Pulling in MEC With Parameter SharingIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2025.352764936:3(437-454)Online publication date: Mar-2025
      • (2024)SODA: An Adaptive Bitrate Controller for Consistent High-Quality Video StreamingProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672260(613-644)Online publication date: 4-Aug-2024
      • (2024)P4BS: Leveraging Passive Measurements From P4 Switches to Dynamically Modify a Router’s Buffer SizeIEEE Transactions on Network and Service Management10.1109/TNSM.2023.330633521:1(1082-1099)Online publication date: Feb-2024
      • (2024)Successor Feature-Based Transfer Reinforcement Learning for Video Rate Adaptation With Heterogeneous QoE PreferencesIEEE Transactions on Multimedia10.1109/TMM.2023.333148726(5340-5357)Online publication date: 2024
      • (2024)Accurate Throughput Prediction for Improving QoE in Mobile Adaptive StreamingIEEE Transactions on Mobile Computing10.1109/TMC.2023.3313592(1-18)Online publication date: 2024
      • (2024)MetaABR: A Meta-Learning Approach on Adaptative Bitrate Selection for Video StreamingIEEE Transactions on Mobile Computing10.1109/TMC.2023.326008623:3(2422-2437)Online publication date: Mar-2024
      • (2023)FedABR: A Personalized Federated Reinforcement Learning Approach for Adaptive Video Streaming2023 IFIP Networking Conference (IFIP Networking)10.23919/IFIPNetworking57963.2023.10186404(1-9)Online publication date: 12-Jun-2023
      • (2023)Sammy: smoothing video traffic to be a friendly internet neighborProceedings of the ACM SIGCOMM 2023 Conference10.1145/3603269.3604839(754-768)Online publication date: 10-Sep-2023
      • (2023)Cross that boundary: Investigating the feasibility of cross-layer information sharing for enhancing ABR decision logic over QUICProceedings of the 33rd Workshop on Network and Operating System Support for Digital Audio and Video10.1145/3592473.3592563(50-57)Online publication date: 7-Jun-2023
      • (2023)Cross-layer Network Bandwidth Estimation for Low-latency Live ABR StreamingProceedings of the 14th Conference on ACM Multimedia Systems10.1145/3587819.3590990(183-193)Online publication date: 7-Jun-2023
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