History-based throughput prediction with Hidden Markov Model in mobile networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Throughput prediction contributes a lot to adaptive bitrate control, adjusting the quality of video streaming accordingly to offer smooth media transmission and save energy at the same time. To solve the problem of throughput prediction for real time communication, this paper puts forward a new history-based throughput prediction method applying Hidden Markov Model in mobile networks. The main purpose of this method is to predict future throughput for real time communication in mobile network. Our novel approach utilizes Hidden Markov Model (HMM) with Gaussian Mixture Model (GMM) to deal with history time series of throughput and judge fluctuation factor with total variance when predicting future throughput. By conducting experiments with the new methodology, we compare the accuracy of the proposed method with three other conventional prediction methods. Results show our proposed method could identify data fluctuation effectively and predict future 100s throughput with high accuracy in various situations.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509015528
DOIs
Publication statusPublished - 2016 Sep 22
Event2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016 - Seattle, United States
Duration: 2016 Jul 112016 Jul 15

Other

Other2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016
CountryUnited States
CitySeattle
Period16/7/1116/7/15

Fingerprint

Hidden Markov models
Wireless networks
Throughput
Video streaming
Communication
Time series
Experiments

Keywords

  • HMM
  • Mobile network
  • Throughput prediction

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Computer Vision and Pattern Recognition

Cite this

Wei, B., Kanai, K., & Katto, J. (2016). History-based throughput prediction with Hidden Markov Model in mobile networks. In 2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016 [7574683] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMEW.2016.7574683

History-based throughput prediction with Hidden Markov Model in mobile networks. / Wei, Bo; Kanai, Kenji; Katto, Jiro.

2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7574683.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wei, B, Kanai, K & Katto, J 2016, History-based throughput prediction with Hidden Markov Model in mobile networks. in 2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016., 7574683, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016, Seattle, United States, 16/7/11. https://doi.org/10.1109/ICMEW.2016.7574683
Wei B, Kanai K, Katto J. History-based throughput prediction with Hidden Markov Model in mobile networks. In 2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7574683 https://doi.org/10.1109/ICMEW.2016.7574683
Wei, Bo ; Kanai, Kenji ; Katto, Jiro. / History-based throughput prediction with Hidden Markov Model in mobile networks. 2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016. Institute of Electrical and Electronics Engineers Inc., 2016.
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