A History-Based TCP Throughput Prediction Incorporating Communication Quality Features by Support Vector Regression for Mobile Network

Bo Wei, Wataru Kawakami, Kenji Kanai, Jiro Katto

研究成果: Conference contribution

1 引用 (Scopus)

抜粋

Throughput prediction is one of good solutions to improve quality of mobile applications (e.g., YouTube or Netflix) for video streaming delivery services in mobile networks. This is because such applications require monitoring the network performances to control content quality, thus guarantee quality of service (QoS) and quality of experience (QoE). In this paper, we propose a history-based TCP throughput prediction method incorporating communication quality features using SVR (Support Vector Regression). By taking history of communication quality features such as historical throughput and Received Signal Strength Indication (RSSI) into consideration, the throughput prediction error can be decreased. We conduct experiments with the proposed method and compare the prediction accuracy with a variety of methods in different scenarios of various moving modes of users. Results show that the proposed model could predict throughput effectively in various scenarios and decrease throughput prediction errors by a maximum of 26.47% compared with other methods.

元の言語English
ホスト出版物のタイトルProceedings - 2017 IEEE International Symposium on Multimedia, ISM 2017
出版者Institute of Electrical and Electronics Engineers Inc.
ページ374-375
ページ数2
2017-January
ISBN(電子版)9781538629369
DOI
出版物ステータスPublished - 2017 12 28
イベント19th IEEE International Symposium on Multimedia, ISM 2017 - Taichung, Taiwan, Province of China
継続期間: 2017 12 112017 12 13

Other

Other19th IEEE International Symposium on Multimedia, ISM 2017
Taiwan, Province of China
Taichung
期間17/12/1117/12/13

ASJC Scopus subject areas

  • Media Technology
  • Sensory Systems

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  • これを引用

    Wei, B., Kawakami, W., Kanai, K., & Katto, J. (2017). A History-Based TCP Throughput Prediction Incorporating Communication Quality Features by Support Vector Regression for Mobile Network. : Proceedings - 2017 IEEE International Symposium on Multimedia, ISM 2017 (巻 2017-January, pp. 374-375). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISM.2017.74