research-article

Enabling adaptive bitrate algorithms in hybrid CDN/P2P networks

Authors:

Jean Le Feuvre,

Paul-Louis Ageneau,

Alexandre StorelliAuthors Info & Claims

MMSys '20: Proceedings of the 11th ACM Multimedia Systems Conference

Pages 54 - 65

https://doi.org/10.1145/3339825.3391859

Published: 27 May 2020 Publication History

Abstract

As video traffic becomes the dominant part of the global Internet traffic, keeping a good quality of experience (QoE) becomes more challenging. To improve QoE, HTTP adaptive streaming with various adaptive bitrate (ABR) algorithms has been massively deployed for video delivery. Based on their required input information, these algorithms can be classified, into buffer-based, throughput-based or hybrid buffer-throughput algorithms. Nowadays, due to their low cost and high scalability, peer-to-peer (P2P) networks have become an efficient alternative for video delivery over the Internet, and many attempts at merging HTTP adaptive streaming and P2P networks have surfaced. However, the impact of merging these two approaches is still not clear enough, and interestingly, the existing HTTP adaptive streaming algorithms lack testing in a P2P environment. In this paper, we address and analyze the main problems raised by the use of the existing HTTP adaptive streaming algorithms in the context of P2P networks. We propose two methodologies to make these algorithms more efficient in P2P networks regardless of the ABR algorithm used, one favoring overall QoE and one favoring P2P efficiency. Additionally, we propose two new metrics to quantify the P2P efficiency for ABR delivery over P2P.

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https://doi.org/10.3390/electronics13071270
Farahani RÇetinkaya ETimmerer CShojafar MGhanbari MHellwagner H(2024)ALIVE: A Latency- and Cost-Aware Hybrid P2P-CDN Framework for Live Video StreamingIEEE Transactions on Network and Service Management10.1109/TNSM.2023.333519021:2(1561-1580)Online publication date: Apr-2024
https://doi.org/10.1109/TNSM.2023.3335190
Liu QHan RLi Y(2023)Utilizing User Bandwidth Resources in Information-Centric Networking through Blockchain-Based Incentive MechanismFuture Internet10.3390/fi1601001116:1(11)Online publication date: 28-Dec-2023
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Index Terms

Enabling adaptive bitrate algorithms in hybrid CDN/P2P networks
1. Information systems
  1. Information systems applications
    1. Multimedia information systems
      1. Multimedia streaming

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cover image ACM Conferences

MMSys '20: Proceedings of the 11th ACM Multimedia Systems Conference

May 2020

403 pages

ISBN:9781450368452

DOI:10.1145/3339825

General Chairs:
Laura Toni
University College London
,
Ali C. Begen
Ozyegin University and Networked Media
,
Program Chairs:
Özgü Alay
University of Oslo and Simula Metropolitan
,
Christian Timmerer
Alpen-Adria-Universität Klagenfurt and Bitmovin

Copyright © 2020 ACM.

Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Published: 27 May 2020

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MMSys '20

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MMSys '20: 11th ACM Multimedia Systems Conference

June 8 - 11, 2020

Istanbul, Turkey

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MMSys '20 Paper Acceptance Rate 18 of 55 submissions, 33%;

Overall Acceptance Rate 176 of 530 submissions, 33%

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Cited By

Geng JFujita S(2024)Enhancing Crowd-Sourced Video Sharing through P2P-Assisted HTTP Video StreamingElectronics10.3390/electronics1307127013:7(1270)Online publication date: 29-Mar-2024
https://doi.org/10.3390/electronics13071270
Farahani RÇetinkaya ETimmerer CShojafar MGhanbari MHellwagner H(2024)ALIVE: A Latency- and Cost-Aware Hybrid P2P-CDN Framework for Live Video StreamingIEEE Transactions on Network and Service Management10.1109/TNSM.2023.333519021:2(1561-1580)Online publication date: Apr-2024
https://doi.org/10.1109/TNSM.2023.3335190
Liu QHan RLi Y(2023)Utilizing User Bandwidth Resources in Information-Centric Networking through Blockchain-Based Incentive MechanismFuture Internet10.3390/fi1601001116:1(11)Online publication date: 28-Dec-2023
https://doi.org/10.3390/fi16010011
Ma ZRoubia SGiroire FUrvoy-Keller G(2023)Q-learning for Waiting Time Control in CDN/V2V Live streaming2023 IFIP Networking Conference (IFIP Networking)10.23919/IFIPNetworking57963.2023.10186429(1-9)Online publication date: 12-Jun-2023
https://doi.org/10.23919/IFIPNetworking57963.2023.10186429
Farahani RAmirpour HTashtarian FBentaleb ATimmerer CHellwagner HZimmermann RTimmerer CGrois DÇetinkaya ENguyen M(2022)RICHTERProceedings of the 1st Mile-High Video Conference10.1145/3510450.3517290(87-88)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1145/3510450.3517290
Yousef HFeuvre JStorelli ATimmerer CGrois DÇetinkaya ENguyen M(2022)ABR-aware prefetching methods in P2PProceedings of the 1st Mile-High Video Conference10.1145/3510450.3517272(92-93)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1145/3510450.3517272
Karagkioules TPaschos GLiakopoulos NFiandrotti ATsilimantos DCagnazzo M(2022)Online Learning for Adaptive Video Streaming in Mobile NetworksACM Transactions on Multimedia Computing, Communications, and Applications10.1145/346081918:1(1-22)Online publication date: 27-Jan-2022
https://dl.acm.org/doi/10.1145/3460819
Zhu GGu W(2022)User Mapping Strategy in Multi-CDN Streaming: A Data-Driven ApproachIEEE Internet of Things Journal10.1109/JIOT.2021.31125619:9(6638-6649)Online publication date: 1-May-2022
https://doi.org/10.1109/JIOT.2021.3112561
Farahani RBentaleb ACetinkaya ETimmerer CZimmermann RHellwagner H(2022)Hybrid P2P-CDN Architecture for Live Video Streaming: An Online Learning ApproachGLOBECOM 2022 - 2022 IEEE Global Communications Conference10.1109/GLOBECOM48099.2022.10001091(1911-1917)Online publication date: 4-Dec-2022
https://doi.org/10.1109/GLOBECOM48099.2022.10001091
Antaris SRafailidis DGidzijauskas S(2021)A Deep Graph Reinforcement Learning Model for Improving User Experience in Live Video Streaming2021 IEEE International Conference on Big Data (Big Data)10.1109/BigData52589.2021.9671949(1787-1796)Online publication date: 15-Dec-2021
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