Design and implementation of user-oriented video streaming service based on machine learning

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

Abstract

We propose a method to determine appropriate quality of service (QoS) dynamically required by users for video streaming services in this paper. In the proposed method, the QoS parameters for the video streaming are determined based on the machine learning algorithm, by using a regression analysis in particular, according to the user requirements, computational/network resources and service provisioning environments. In this paper, we describe the design and implementation of our method. Furthermore, we confirm the feasibility of our proposed method through an experiment of a prototype system.

Original languageEnglish
Title of host publicationProceedings of 2016 IEEE 15th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages111-116
Number of pages6
ISBN (Electronic)9781509038466
DOIs
Publication statusPublished - 2017 Feb 21
Event15th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2016 - Stanford, United States
Duration: 2016 Aug 222016 Aug 23

Other

Other15th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2016
CountryUnited States
CityStanford
Period16/8/2216/8/23

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Artificial Intelligence
  • Software
  • Computer Vision and Pattern Recognition
  • Information Systems

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    Oide, M., Takahashi, A., Abe, T., & Suganuma, T. (2017). Design and implementation of user-oriented video streaming service based on machine learning. In Proceedings of 2016 IEEE 15th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2016 (pp. 111-116). [7862023] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCI-CC.2016.7862023