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首页> 外文期刊>International journal of software science and computational intelligence >User-Oriented Video Streaming Service Based on Passive Aggressive Learning
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User-Oriented Video Streaming Service Based on Passive Aggressive Learning

机译:基于被动积极学习的面向用户的视频流服务

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摘要

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, computationaletwork 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.
机译:作者提出了一种方法,可以动态确定用户为视频流服务所需的适当服务质量(QoS)。在提出的方法中,根据用户需求,计算/网络资源和服务提供环境,基于被动积极学习确定视频比特率作为QoS参数,被动学习是一种用于回归问题的在线学习算法。而且,该方法使得可以通过使用优化解决方案来提供适当的QoS。在本文中,作者描述了该方法的设计和实现,然后通过实验证实了该方法的可行性。

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