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Practical, Real-time Centralized Control for CDN-based Live Video Delivery

Published: 17 August 2015 Publication History

Abstract

Live video delivery is expected to reach a peak of 50 Tbps this year. This surging popularity is fundamentally changing the Internet video delivery landscape. CDNs must meet users' demands for fast join times, high bitrates, and low buffering ratios, while minimizing their own cost of delivery and responding to issues in real-time. Wide-area latency, loss, and failures, as well as varied workloads ("mega-events" to long-tail), make meeting these demands challenging.
An analysis of video sessions concluded that a centralized controller could improve user experience, but CDN systems have shied away from such designs due to the difficulty of quickly handling failures, a requirement of both operators and users. We introduce VDN, a practical approach to a video delivery network that uses a centralized algorithm for live video optimization. VDN provides CDN operators with real-time, fine-grained control. It does this in spite of challenges resulting from the wide-area (e.g., state inconsistency, partitions, failures) by using a hybrid centralized+distributed control plane, increasing average bitrate by 1.7x and decreasing cost by 2x in different scenarios.

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cover image ACM Conferences
SIGCOMM '15: Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication
August 2015
684 pages
ISBN:9781450335423
DOI:10.1145/2785956
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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Publication History

Published: 17 August 2015

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Author Tags

  1. CDNs
  2. central optimization
  3. hybrid control
  4. live video

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SIGCOMM '15
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SIGCOMM '15: ACM SIGCOMM 2015 Conference
August 17 - 21, 2015
London, United Kingdom

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SIGCOMM '15 Paper Acceptance Rate 40 of 242 submissions, 17%;
Overall Acceptance Rate 462 of 3,389 submissions, 14%

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  • (2023)FlowBot: A Learning-Based Co-bottleneck Flow Detector for Video Servers2023 IEEE 31st International Conference on Network Protocols (ICNP)10.1109/ICNP59255.2023.10355638(1-12)Online publication date: 10-Oct-2023
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