Titlebook: Video Processing in the Cloud; Rafael Silva Pereira,Karin K. Breitman Book 2011 Rafael Silva Pereira 2011 Cloud computing.Distributed syst

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The Split&Merge Architecture,cture generalizes the Map-Reduce paradigm, combining it to a provisioning component that dynamically launches virtual machines in private clusters or in the Cloud, and provides an efficient solution that contemplates relevant aspects of intense processing video applications.

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Case Studies,ices platform. The first one was a video transcoding application used by . to generate different video formats, for Internet distribution, from a high definition input. The second one was an OCR application for automatic sports video annotation, which detects available information inside video frame

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Limitations,, and some limitations that restrict its usage. In this chapter we discuss how the network, inside and outside the Cloud platform, the architecture itself, and the Cloud platforms heterogeneity, could reduce the Split&Merge efficiency or even restricts its usage.

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Background,also relevant to analyze the paradigms that could be used in this task. The Map Reduce approach, proposed by Dean and Ghemawat, is an efficient way for processing very large datasets using a computer cluster and, more recently, cloud infrastructures.

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