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User-Oriented Video Streaming Service Based on Passive Aggressive Learning
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Author(s): Makoto Oide (Graduate School of Information Sciences, Tohoku University, Sendai, Japan), Akiko Takahashi (National Institute of Technology, Sendai College, Sendai, Japan), Toru Abe (Cyberscience Center/RIEC, Graduate School of Information Sciences, Tohoku University, Sendai, Japan)and Takuo Suganuma (Cyberscience Center/RIEC, Graduate School of Information Sciences, Tohoku University, Sendai, Japan)
Copyright: 2020
Pages: 21
Source title:
Cognitive Analytics: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-2460-2.ch025
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Abstract
The authors propose a method to dynamically determine appropriate quality of service (QoS) required by users for video streaming services. In the proposed method, the video bit rate as the QoS parameter is determined based on the passive aggressive learning, which is an online learning algorithm for a regression problem, according to the user requirements, computational/network resources and service provisioning environments. Moreover, the method makes it possible to provide appropriate QoS by using optimization solution. In this paper, the authors describe the design and implementation of the method, then confirm the feasibility of the proposed method through the experiments.
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