Capacity analysis of peer-to-peer adaptive streaming

Yang Xu, Yong Liu, Keith Ross

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

Abstract

Adaptive streaming, such as Dynamic Adaptive Streaming over HTTP (DASH), has been widely deployed to provide uninterrupted video streaming service to users with dynamic network conditions. In this paper, we analytically study the potential of using P2P in conjunction with adaptive streaming. We first study the capacity of P2P adaptive streaming by developing utility maximization models that take into account peer heterogeneity, taxation-based incentives, multi-version videos at discrete rates. We further develop stochastic models to study the performance of P2P adaptive streaming in face of bandwidth variations and peer churn. Through analysis and simulations, we demonstrate that incentive-compatible video sharing between peers can be easily achieved with simple video coding and distribution designs. P2P adaptive streaming not only significantly reduces the load on the servers, but also improves the stability of user-perceived video quality in the face of dynamic bandwidth changes.

Original languageEnglish (US)
Title of host publication13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 - Proceedings
PublisherIEEE Computer Society
ISBN (Print)9781479905218
DOIs
StatePublished - 2013
Event13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 - Trento, Italy
Duration: Sep 9 2013Sep 11 2013

Other

Other13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013
CountryItaly
CityTrento
Period9/9/139/11/13

Fingerprint

Bandwidth
HTTP
Video streaming
Stochastic models
Taxation
Image coding
Servers

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Xu, Y., Liu, Y., & Ross, K. (2013). Capacity analysis of peer-to-peer adaptive streaming. In 13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 - Proceedings [6688695] IEEE Computer Society. https://doi.org/10.1109/P2P.2013.6688695

Capacity analysis of peer-to-peer adaptive streaming. / Xu, Yang; Liu, Yong; Ross, Keith.

13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 - Proceedings. IEEE Computer Society, 2013. 6688695.

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

Xu, Y, Liu, Y & Ross, K 2013, Capacity analysis of peer-to-peer adaptive streaming. in 13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 - Proceedings., 6688695, IEEE Computer Society, 13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013, Trento, Italy, 9/9/13. https://doi.org/10.1109/P2P.2013.6688695
Xu Y, Liu Y, Ross K. Capacity analysis of peer-to-peer adaptive streaming. In 13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 - Proceedings. IEEE Computer Society. 2013. 6688695 https://doi.org/10.1109/P2P.2013.6688695
Xu, Yang ; Liu, Yong ; Ross, Keith. / Capacity analysis of peer-to-peer adaptive streaming. 13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 - Proceedings. IEEE Computer Society, 2013.
@inproceedings{8c7571e6393d45f2bbe98563d6085be1,
title = "Capacity analysis of peer-to-peer adaptive streaming",
abstract = "Adaptive streaming, such as Dynamic Adaptive Streaming over HTTP (DASH), has been widely deployed to provide uninterrupted video streaming service to users with dynamic network conditions. In this paper, we analytically study the potential of using P2P in conjunction with adaptive streaming. We first study the capacity of P2P adaptive streaming by developing utility maximization models that take into account peer heterogeneity, taxation-based incentives, multi-version videos at discrete rates. We further develop stochastic models to study the performance of P2P adaptive streaming in face of bandwidth variations and peer churn. Through analysis and simulations, we demonstrate that incentive-compatible video sharing between peers can be easily achieved with simple video coding and distribution designs. P2P adaptive streaming not only significantly reduces the load on the servers, but also improves the stability of user-perceived video quality in the face of dynamic bandwidth changes.",
author = "Yang Xu and Yong Liu and Keith Ross",
year = "2013",
doi = "10.1109/P2P.2013.6688695",
language = "English (US)",
isbn = "9781479905218",
booktitle = "13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 - Proceedings",
publisher = "IEEE Computer Society",

}

TY - GEN

T1 - Capacity analysis of peer-to-peer adaptive streaming

AU - Xu, Yang

AU - Liu, Yong

AU - Ross, Keith

PY - 2013

Y1 - 2013

N2 - Adaptive streaming, such as Dynamic Adaptive Streaming over HTTP (DASH), has been widely deployed to provide uninterrupted video streaming service to users with dynamic network conditions. In this paper, we analytically study the potential of using P2P in conjunction with adaptive streaming. We first study the capacity of P2P adaptive streaming by developing utility maximization models that take into account peer heterogeneity, taxation-based incentives, multi-version videos at discrete rates. We further develop stochastic models to study the performance of P2P adaptive streaming in face of bandwidth variations and peer churn. Through analysis and simulations, we demonstrate that incentive-compatible video sharing between peers can be easily achieved with simple video coding and distribution designs. P2P adaptive streaming not only significantly reduces the load on the servers, but also improves the stability of user-perceived video quality in the face of dynamic bandwidth changes.

AB - Adaptive streaming, such as Dynamic Adaptive Streaming over HTTP (DASH), has been widely deployed to provide uninterrupted video streaming service to users with dynamic network conditions. In this paper, we analytically study the potential of using P2P in conjunction with adaptive streaming. We first study the capacity of P2P adaptive streaming by developing utility maximization models that take into account peer heterogeneity, taxation-based incentives, multi-version videos at discrete rates. We further develop stochastic models to study the performance of P2P adaptive streaming in face of bandwidth variations and peer churn. Through analysis and simulations, we demonstrate that incentive-compatible video sharing between peers can be easily achieved with simple video coding and distribution designs. P2P adaptive streaming not only significantly reduces the load on the servers, but also improves the stability of user-perceived video quality in the face of dynamic bandwidth changes.

UR - http://www.scopus.com/inward/record.url?scp=84893239959&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84893239959&partnerID=8YFLogxK

U2 - 10.1109/P2P.2013.6688695

DO - 10.1109/P2P.2013.6688695

M3 - Conference contribution

AN - SCOPUS:84893239959

SN - 9781479905218

BT - 13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 - Proceedings

PB - IEEE Computer Society

ER -