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Optimizing power consumption of mobile devices for video streaming over 4G LTE networks

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Abstract

While the video streaming technique and 4G LTE networks are developing rapidly, the advancement of the battery technology, however, is relatively slow. Existing works have paid much attention to understanding the power consumption in general 4G LTE networks, while few attention has been paid to reducing the power consumption for online video streaming in 4G LTE networks. Our previous work based on the real experimental platform showed that, the saving room in the network part is large, the transmission pattern and the number of RRC tails could be promising for optimizing the power consumption. In this paper, we attempt to develop efficient optimization strategies to save the energy cost of mobile devices for online video streaming over 4G LTE networks. This problem is clearly important and also interesting, while it is challenging, due to various reasons such as the uncertainty of users’ behavior modes. To alleviate the challenges, we suggest a self-adaptive method that can allow us to adjust various parameters dynamically and efficiently, so as to achieve a relatively small energy consumption. We give the rigorous theoretical analysis for the proposed method, and conduct extensive experiments to validate its effectiveness. The experimental results show that the proposed method consistently outperforms the classical method as well as other competitors adapted from existing methods.

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Notes

  1. When a user u enjoys the online video streaming service, the video streaming player downloads the video segments periodically. This implies that many downloading sessions shall be involved in this process; and usually the “downloading session” is called “segment fetching session”.

  2. When one plays back an online video, the video may last for a relative long time. In this paper, the warm-up stage refers to the early stage of the video being played back. In the warm-up stage, the number of video segments in a single segment fetching session is relatively small.

  3. Here the term “initial” maximum number refers to the value before enlarging the buffer.

  4. Note that here b m is essentially equal to \(b_{m}^{\prime }\).

  5. Remark that, in the traditional implementation, b m − b t = 1, and so \(\frac {n - b_{m}}{b_{m} - b_{t}} = (n - b_{m})\).

  6. Here the skip duration refers to the step length of each skip, when a user drags the process bar.

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Acknowledgements

We would like to acknowledge the editors and anonymous reviewers for their instructive suggestions. Also, we gratefully acknowledge the warm help of Prof. Chunyi Peng and Prof. Sheng Wei, who have offered us valuable advices. This work was sponsored by the National Basic Research (“973”) Program of China (2015CB352403), the National Natural Science Foundation of China (61261160502, 61272099, 61472453, 61602166, U1501252, U1611264, and U1401256), the Open Project of Beijing Key Laboratory of Big Data Management and Analysis Method, the Scientific Innovation Act of STCSM (13511504200), and the EU FP7 CLIMBER project (PIRSES-GA-2012-318939).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

    Jingyu Zhang, Yuanyi Chen & Minyi Guo

  2. Guangdong Key Laboratory of Big Data Analysis and Processing, School of Data and Computer Science, Sun Yat-Sen University, Guangzhou, China

    Zhi-Jie Wang & Jian Yin

  3. Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China

    Zhi-Jie Wang

  4. College of Computer Science and Electronic Engineering, Hunan University, Changsha, China

    Zhe Quan

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  1. Jingyu Zhang
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Correspondence to Zhi-Jie Wang or Minyi Guo.

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This article is part of the Topical Collection: Special Issue on Big Data Networking

Guest Editors: Xiaofei Liao, Song Guo, Deze Zeng, and Kun Wang

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Zhang, J., Wang, ZJ., Quan, Z. et al. Optimizing power consumption of mobile devices for video streaming over 4G LTE networks. Peer-to-Peer Netw. Appl. 11, 1101–1114 (2018). https://doi.org/10.1007/s12083-017-0580-6

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