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  1. Proceedings of the 25th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV '15)
  2. Thunder crystal: a novel crowdsourcing-based content distribution platform
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Content-adaptive display power saving in internet mobile streaming
Exploitation of producer intent in relation to bandwidth and QoE for online video streaming services
When on-the-fly erasure code makes late video decoding happen
Last N: relevance-based selectivity for forwarding video in multimedia conferences
DASH fast start using HTTP/2
A fuzzy-based rate adaptation controller for DASH
VAS: a video adaptation service to support mobile video
Thunder crystal: a novel crowdsourcing-based content distribution platform
A logical memory model for scaling parallel multimedia workloads
On crowdsourced interactive live streaming: a Twitch.tv-based measurement study
Towards bridging online game playing and live broadcasting: design and optimization
A taxonomy for player actions with latency in network games

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Thunder crystal: a novel crowdsourcing-based content distribution platform

Content Provider ACM Digital Library
Author Jing, Mi Chen, Liang Zhou, Yipeng Ma, Richard T. B.
Abstract Content distribution, especially the distribution of video content, unavoidably consumes bandwidth resource heavily. Internet content providers (ICP) spend lots of money to buy content distribution network (CDN) service. By deploying thousands of edge servers close to end users, CDN companies are able to distribute content efficiently. In lieu of traditional CDN systems, we implement a crowdsourcing-based content distribution system, Thunder Crystal, which utilizes agents' upload bandwidth to amplify the content distribution capacity. Agents are well motivated to contribute storage and upload bandwidth to the system by rebated cash. As far as we know, this is a novel system that has not been studied before. In this work, we will present its design principles first. Then, we study agent behavior and methods to evaluate system efficiency and user efficiency. We evaluate the system by simulations, and observe that agents are well motivated to keep online most of the time and amplify the content distribution capacity by 10~20 times.
Starting Page 43
Ending Page 48
Page Count 6
File Format PDF
ISBN 9781450333528
DOI 10.1145/2736084.2736085
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2015-03-18
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Crowdsourcing Content distribution networking
Content Type Text
Resource Type Article
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