媒体网格流媒体质量监测与分析的多智能体方法

Xiaorong Li, W. Jie, Xiuju FU, H. Chan, Quoc-Thuan Ho, T. Hung, D. Ong, S. Turner, B. Veeravalli
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引用次数: 2

摘要

媒体流是一项很有前途的技术,它可以快速、自适应地传输媒体内容,并允许客户在线观看视频,而无需等待整个多媒体文件完全下载。在本文中,我们解决了大规模网络上的流质量测量和评估问题。提出了一种多智能体流媒体质量监控与分析系统(MASQMA),该系统能够实时监控和分析大规模IP网络上的流媒体质量。该系统基于分散的基础设施,具有可扩展性和灵活性,可以满足多种流媒体应用,而不会增加当前流媒体系统的处理负担。它允许用户使用各种质量指标实时监控QoS。我们对广域网中常见的带宽波动、丢包、帧抖动等情况下的性能进行了实验研究。结果表明,多智能体体系结构在实时监控和分析流质量方面具有实用性和灵活性。
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A Multi-Agent Method for Streaming Quality Monitoring and Analysis over Media Grid
Media streaming is a promising technology which enables fast and adaptive delivery of media contents and allows clients to view videos online without waiting for the entire multimedia files to be completely downloaded. In this paper, we address the issue of streaming quality measurement and assessment over a large scale network. We propose a multiagent system for streaming quality monitoring and analysis (MASQMA) which can real-time monitor and analyze the quality of media streaming over a large scale IP network. Based on a decentralized infrastructure, such a system is scalable and flexible to meet versatile streaming applications without increasing the processing burden on the current media streaming systems. It allows users to real-time monitor the QoS with a variety of quality metrics. We conduct experiments and study the performance under various situations (e.g., bandwidth fluctuations, packet loss, and frame jitter) which are frequently encountered in Wide Area Networks. The results show the multi-agent architecture is practical and flexible to monitor and analyze streaming quality in real time.
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