TransFetch

A Viewing Behavior Driven Video Distribution Framework in Public Transport

Fangzhou Jiang, Zhi Liu, Kanchana Thilakarathna, Zhenyu Li, Yusheng Ji, Aruna Seneviratne

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Mobile video traffic is exploding and it is particularly challenging to stream video when high density of users are "on the move", e.g., in public transport systems. It becomes increasingly problematic as video traffic is predicted to account for more than 80% of Internet traffic by 2019. This will be exacerbated by factors such as cellular network coverage issues and unstable network throughput due to high speed mobility. By exploiting the predictable public transport mobility patterns, spatio-temporal correlation of user interests and users' video viewing behaviors, we proposed TransFetch which uses intelligent caching on-board the public transport vehicles as well as a novel video chunk placement algorithm. We show through extensive simulations, that TransFetch reduces the system cellular data usage by up to 45% and improves the quality of video streaming by up to 35%. Finally, we demonstrate the practical feasibility of TransFetch by implementing caching units on a Raspberry-Pi and a mobile app on an Android device.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE 41st Conference on Local Computer Networks, LCN 2016
PublisherIEEE Computer Society
Pages147-155
Number of pages9
ISBN (Electronic)9781509020546
DOIs
Publication statusPublished - 2016 Dec 22
Event41st IEEE Conference on Local Computer Networks, LCN 2016 - Dubai, United Arab Emirates
Duration: 2016 Nov 72016 Nov 10

Other

Other41st IEEE Conference on Local Computer Networks, LCN 2016
CountryUnited Arab Emirates
CityDubai
Period16/11/716/11/10

Fingerprint

Video streaming
Application programs
Throughput
Internet
Android (operating system)

Keywords

  • Mobile Multimedia
  • Multimedia Transport and Delivery
  • Stream Quality
  • User Behavior

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture

Cite this

Jiang, F., Liu, Z., Thilakarathna, K., Li, Z., Ji, Y., & Seneviratne, A. (2016). TransFetch: A Viewing Behavior Driven Video Distribution Framework in Public Transport. In Proceedings - 2016 IEEE 41st Conference on Local Computer Networks, LCN 2016 (pp. 147-155). [7796773] IEEE Computer Society. https://doi.org/10.1109/LCN.2016.27

TransFetch : A Viewing Behavior Driven Video Distribution Framework in Public Transport. / Jiang, Fangzhou; Liu, Zhi; Thilakarathna, Kanchana; Li, Zhenyu; Ji, Yusheng; Seneviratne, Aruna.

Proceedings - 2016 IEEE 41st Conference on Local Computer Networks, LCN 2016. IEEE Computer Society, 2016. p. 147-155 7796773.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Jiang, F, Liu, Z, Thilakarathna, K, Li, Z, Ji, Y & Seneviratne, A 2016, TransFetch: A Viewing Behavior Driven Video Distribution Framework in Public Transport. in Proceedings - 2016 IEEE 41st Conference on Local Computer Networks, LCN 2016., 7796773, IEEE Computer Society, pp. 147-155, 41st IEEE Conference on Local Computer Networks, LCN 2016, Dubai, United Arab Emirates, 16/11/7. https://doi.org/10.1109/LCN.2016.27
Jiang F, Liu Z, Thilakarathna K, Li Z, Ji Y, Seneviratne A. TransFetch: A Viewing Behavior Driven Video Distribution Framework in Public Transport. In Proceedings - 2016 IEEE 41st Conference on Local Computer Networks, LCN 2016. IEEE Computer Society. 2016. p. 147-155. 7796773 https://doi.org/10.1109/LCN.2016.27
Jiang, Fangzhou ; Liu, Zhi ; Thilakarathna, Kanchana ; Li, Zhenyu ; Ji, Yusheng ; Seneviratne, Aruna. / TransFetch : A Viewing Behavior Driven Video Distribution Framework in Public Transport. Proceedings - 2016 IEEE 41st Conference on Local Computer Networks, LCN 2016. IEEE Computer Society, 2016. pp. 147-155
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