With the advent of high-speed networking technology and multimedia compression, various network-based multimedia services have become available [29]. Clients can download music, send/receive multimedia emails, browse multimedia material in eLibraries and enjoy high quality movies on-line. Media streaming [24] is one of the most popular real-time multimedia services. It enables clients to view multimedia content online without completely downloading it. In addition, it can support complete flexibility in presentation by controlling playback — in other words, clients can alter the presentation by using Video Cassette Recorder (VCR)-like control facilities, such as ‘rewind’, ‘fast-forward’, ‘pause’, and the like. However, rendering high quality media streaming via networks is still a challenging task, not only due to the large size of video files, but also because of the critical requirements to guarantee Quality-of-Service (QoS) — these being delay, loss rate, jitter, and so forth — for distributing real-time media streams over networks.
The Chapter is organized as follows. Section 2 describes related work. Section 3 presents a media grid framework. Section 4 describes the data mining strategy for bandwidth prediction in media grids. Experiments of bandwidth prediction are presented in Sect. 5. Sect. 6 concludes the Chapter.
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Fu, X., Li, X., Wang, L., Ong, D., Turner, S.J. (2008). Data Mining in QoS-Aware Media Grids. In: Fulcher, J., Jain, L.C. (eds) Computational Intelligence: A Compendium. Studies in Computational Intelligence, vol 115. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78293-3_16
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