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Improving the application performance of Loki via algorithm optimization

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Abstract

Loki is a state-of-the-art adaptive bitrate algorithm for the transmission of real-time-communication (RTC) video. It fuses traditional heuristic methods with a learning-based model to maximize the quality of experience (QoE) under diverse network conditions. However, a recurring rebound pattern is observed in Loki’s decision-making process where the decision frequently oscillates between the two boundaries of the action space, making Loki fail to adapt to the fluctuating network bandwidth. To address this issue, we propose Loki+, which improves both the fusion mechanism and the design of the learning-based actor. Specifically, we replace the element-wise multiplication with a simple but effective trend fusion and further optimize the design of reward and loss functions for training Loki+. Extensive simulation results show that Loki+ significantly improves the QoE in the aspects of reducing the stall rate by 20%\(\sim\)60% and the frame delay by 3.5%\(\sim\)30.5% while maintaining a similar sending bitrate or video quality, compared with Loki.

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Data availability

The data that support the findings of this study are available on request from the corresponding author HC, upon reasonable request.

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Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (62101241), Jiangsu Provincial Double-Innovation Doctor Program (JSSCBS20210001), and Changzhou Power Supply Branch of State Grid Jiangsu Electric Power Co., Ltd.(SGJSCZ00KJJS2311209).

Funding

Research grants from the National Natural Science Foundation of China (62101241), Jiangsu Provincial Double-Innovation Doctor Program (JSSCBS20210001), and Changzhou Power Supply Branch of State Grid Jiangsu Electric Power Co., Ltd. ( SGJSCZ00KJJS2311209).

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Author notes

  1. Wenming Zhu and Wen**g Su have contributed equally to this work.

Authors and Affiliations

  1. Changzhou Power Supply Branch of State Grid Jiangsu Electric Power Co., Ltd., Junqian Street, Changzhou, 213100, Jiangsu Province, China

    Wenming Zhu & Kai Yang

  2. School of Electronic Science and Engineering, Nan**g University, **anlin Street, Nan**g, 210023, Jiangsu Province, China

    Wen**g Su & Hao Chen

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  1. Wenming Zhu
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  2. Wen**g Su
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  3. Kai Yang
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  4. Hao Chen
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Contributions

Material preparation, data collection, and analysis were performed by WZ, WS, and KY. Conceptualization and methodology were performed by WS and HC. The first draft of the manuscript was written by WS and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Hao Chen.

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Communicated by B. Bao.

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Zhu, W., Su, W., Yang, K. et al. Improving the application performance of Loki via algorithm optimization. Multimedia Systems 30, 2 (2024). https://doi.org/10.1007/s00530-023-01197-5

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