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

4 被引用数 (Scopus)

抄録

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.

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

出版物シリーズ

名前Proceedings - 2017 IEEE International Symposium on Multimedia, ISM 2017
2017-January

Other

Other19th IEEE International Symposium on Multimedia, ISM 2017
国/地域Taiwan, Province of China
CityTaichung
Period17/12/1117/12/13

ASJC Scopus subject areas

  • メディア記述
  • 感覚系

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