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A Reinforcement Learning Framework for Multi-source Adaptive Streaming

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Computational Collective Intelligence (ICCCI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12876))

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Abstract

Dynamic adaptive streaming over HTTP (DASH) is widely used in video streaming recently. With DASH, a video is stored in multiple equal-playing-time chunks with different quality levels. Video chunks are in-order delivered from a single source over a path in traditional DASH. The adaptation function in video player chooses a suitable quality level to request depending on current network status for each video chunk. In modern networks such as content delivery networks, edge caching, content-centric networks, etc., popular video contents are replicated at multiple cache nodes. Utilizing multiple sources for video streaming is investigated in this paper. We propose a reinforcement learning based algorithm, called RAMS, for rate adaptation in multi-source video streaming. The proposed algorithm outperforms the other notable adaptation methods.

This research is funded by Vietnam National University HoChiMinh City (VNU-HCM) under grant number DS2020-28-01.

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Author information

Authors and Affiliations

  1. International University, Ho Chi Minh City, Vietnam

    Nghia T. Nguyen, Phuong L. Vo, Thi Thanh Sang Nguyen & Quan M. Le

  2. Vietnam National University, Ho Chi Minh City, Vietnam

    Nghia T. Nguyen, Phuong L. Vo, Thi Thanh Sang Nguyen & Quan M. Le

  3. Kyung Hee University, Yongin, Korea

    Cuong T. Do

  4. Wroclaw University of Science and Technology, Wrocław, Poland

    Ngoc-Thanh Nguyen

Authors
  1. Nghia T. Nguyen
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  2. Phuong L. Vo
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  3. Thi Thanh Sang Nguyen
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  4. Quan M. Le
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  5. Cuong T. Do
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  6. Ngoc-Thanh Nguyen
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Corresponding author

Correspondence to Phuong L. Vo .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Democritus University of Thrace, Kimmeria, Xanthi, Greece

    Lazaros Iliadis

  3. University of Piraeus, Piraeus, Greece

    Ilias Maglogiannis

  4. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Nguyen, N.T., Vo, P.L., Nguyen, T.T.S., Le, Q.M., Do, C.T., Nguyen, NT. (2021). A Reinforcement Learning Framework for Multi-source Adaptive Streaming. In: Nguyen, N.T., Iliadis, L., Maglogiannis, I., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2021. Lecture Notes in Computer Science(), vol 12876. Springer, Cham. https://doi.org/10.1007/978-3-030-88081-1_31

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  • DOI: https://doi.org/10.1007/978-3-030-88081-1_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-88080-4

  • Online ISBN: 978-3-030-88081-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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