Adaptive bit-rate video streaming on named data networking with active throughput estimation
© 2018 Association for Computing Machinery. Named Data Networking (NDN) has been recently introduced as a new future network architecture. The end-to-end throughput estimation for adaptive bit-rate video streaming on NDN is one of the most challenging topics. Specifically, the end-to-end throughput...
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th-cmuir.6653943832-626602018-11-29T07:38:39Z Adaptive bit-rate video streaming on named data networking with active throughput estimation Kanin Poobai Suphakit Awiphan Jiro Katto Computer Science © 2018 Association for Computing Machinery. Named Data Networking (NDN) has been recently introduced as a new future network architecture. The end-to-end throughput estimation for adaptive bit-rate video streaming on NDN is one of the most challenging topics. Specifically, the end-to-end throughput estimation on NDN appears to be unreliable, since the provider of content is unknown to the consumer. Moreover, partial caching on NDN router's Content Store could temporarily lead to packet loss due to throughput overestimation. In this paper, we present an active Interest adaptation scheme which operates by proactively estimating the throughput in a hop-by-hop fashion. The consumer node is then assisted with the most recent available end-to-end bandwidth. Therefore, the video player can promptly adapt to the change of network condition. The implementation evaluation using NDN-JS and DASH-JS on the setup network demonstrate that our proposed solution provides better average stream bit-rate and consumes less network bandwidth than the traditional system. 2018-11-29T07:38:39Z 2018-11-29T07:38:39Z 2018-04-27 Conference Proceeding 2-s2.0-85056517811 10.1145/3209914.3209929 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85056517811&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/62660 |
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Computer Science Kanin Poobai Suphakit Awiphan Jiro Katto Adaptive bit-rate video streaming on named data networking with active throughput estimation |
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© 2018 Association for Computing Machinery. Named Data Networking (NDN) has been recently introduced as a new future network architecture. The end-to-end throughput estimation for adaptive bit-rate video streaming on NDN is one of the most challenging topics. Specifically, the end-to-end throughput estimation on NDN appears to be unreliable, since the provider of content is unknown to the consumer. Moreover, partial caching on NDN router's Content Store could temporarily lead to packet loss due to throughput overestimation. In this paper, we present an active Interest adaptation scheme which operates by proactively estimating the throughput in a hop-by-hop fashion. The consumer node is then assisted with the most recent available end-to-end bandwidth. Therefore, the video player can promptly adapt to the change of network condition. The implementation evaluation using NDN-JS and DASH-JS on the setup network demonstrate that our proposed solution provides better average stream bit-rate and consumes less network bandwidth than the traditional system. |
format |
Conference Proceeding |
author |
Kanin Poobai Suphakit Awiphan Jiro Katto |
author_facet |
Kanin Poobai Suphakit Awiphan Jiro Katto |
author_sort |
Kanin Poobai |
title |
Adaptive bit-rate video streaming on named data networking with active throughput estimation |
title_short |
Adaptive bit-rate video streaming on named data networking with active throughput estimation |
title_full |
Adaptive bit-rate video streaming on named data networking with active throughput estimation |
title_fullStr |
Adaptive bit-rate video streaming on named data networking with active throughput estimation |
title_full_unstemmed |
Adaptive bit-rate video streaming on named data networking with active throughput estimation |
title_sort |
adaptive bit-rate video streaming on named data networking with active throughput estimation |
publishDate |
2018 |
url |
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85056517811&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/62660 |
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