research-article

PiTree: Practical Implementation of ABR Algorithms Using Decision Trees

Authors:

Mingwei XuAuthors Info & Claims

MM '19: Proceedings of the 27th ACM International Conference on Multimedia

Pages 2431 - 2439

https://doi.org/10.1145/3343031.3350866

Published: 15 October 2019 Publication History

Abstract

Major commercial client-side video players employ adaptive bitrate (ABR) algorithms to improve user quality of experience (QoE). With the evolvement of ABR algorithms, increasingly complex methods such as neural networks have been adopted to pursue better performance. However, these complex methods are too heavyweight to be directly implemented in client devices, especially mobile phones with very limited resources. Existing solutions suffer from a trade-off between algorithm performance and deployment overhead. To make the implementation of sophisticated ABR algorithms practical, we propose PiTree, a general, high-performance and scalable framework that can faithfully convert sophisticated ABR algorithms into lightweight decision trees to reduce deployment overhead. We also provide a theoretical upper bound on the optimization loss during the conversion. Evaluation results on three representative ABR algorithms demonstrate that PiTree could faithfully convert ABR algorithms into decision trees with <3% average performance degradation. Moreover, comparing to original implementation solutions, PiTree could save operating expenses for large content providers.

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Zhang YZhang WDu HYan CLiu LZheng Q(2024)FHVAC: Feature-Level Hybrid Video Adaptive Configuration for Machine-Centric Live StreamingIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2024.337204635:5(780-795)Online publication date: May-2024
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Lv GWu QTan QWang WLi ZXie G(2024)Accurate Throughput Prediction for Improving QoE in Mobile Adaptive StreamingIEEE Transactions on Mobile Computing10.1109/TMC.2023.3313592(1-18)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3313592
Xu HLi LWang LSong F(2024)Congestion Control as a Service: Towards Low Latency Mobile Uploading2024 IEEE/ACM 32nd International Symposium on Quality of Service (IWQoS)10.1109/IWQoS61813.2024.10682903(1-10)Online publication date: 19-Jun-2024
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Index Terms

PiTree: Practical Implementation of ABR Algorithms Using Decision Trees
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Reinforcement learning
        Sequential decision making
2. Information systems
  1. Information systems applications
    1. Multimedia information systems
      1. Multimedia streaming

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cover image ACM Conferences

MM '19: Proceedings of the 27th ACM International Conference on Multimedia

October 2019

2794 pages

ISBN:9781450368896

DOI:10.1145/3343031

General Chairs:
Laurent Amsaleg
CNRS-IRISA, France
,
Benoit Huet
EURECOM, France
,
Martha Larson
Radboud University and TU Delft (Netherlands)
,
Program Chairs:
Guillaume Gravier
CNRS-IRISA, France
,
Hayley Hung
Delft University of Technology Netherlands
,
Chong-Wah Ngo
City University of Hong Kong Hong Kong
,
Wei Tsang Ooi
National University of Singapore Singapore

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Published: 15 October 2019

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National Natural Science Foundation of China
National Key R&D Program of China

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MM '19

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MM '19: The 27th ACM International Conference on Multimedia

October 21 - 25, 2019

Nice, France

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MM '19 Paper Acceptance Rate 252 of 936 submissions, 27%;

Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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https://doi.org/10.1109/TPDS.2024.3372046
Lv GWu QTan QWang WLi ZXie G(2024)Accurate Throughput Prediction for Improving QoE in Mobile Adaptive StreamingIEEE Transactions on Mobile Computing10.1109/TMC.2023.3313592(1-18)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3313592
Xu HLi LWang LSong F(2024)Congestion Control as a Service: Towards Low Latency Mobile Uploading2024 IEEE/ACM 32nd International Symposium on Quality of Service (IWQoS)10.1109/IWQoS61813.2024.10682903(1-10)Online publication date: 19-Jun-2024
https://doi.org/10.1109/IWQoS61813.2024.10682903
Wu WYuan JMa SYang M(2024)AP-assisted adaptive video streaming in wireless networks with high-density clientsComputer Communications10.1016/j.comcom.2024.03.001219(53-63)Online publication date: Apr-2024
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Al-Mashhadani AMu MAl-Sharbaz A(2022)Quality of Experience Experimentation Prediction Framework through Programmable Network ManagementNetwork10.3390/network20400302:4(500-518)Online publication date: 8-Oct-2022
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