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    Catholic University of Rio de Janeiro (PUC-Rio)

    An Architecture for Distributed High Performance Video Processing in the Cloud

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    Video processing applications are notably data intense, time, and resource consuming. Upfront infrastructure investment is usually high, specially when dealing with applications where time-to- market is a crucial requirement, e.g., breaking news and journalism. Such infrastructures are often inefficient, because due to demand variations, resources may end up idle a good portion of the time. In this paper, we propose the Split&Merge architecture for high performance video processing, a generalization of the MapReduce paradigm that rationalizes the use of resources by exploring on demand computing. To illustrate the approach, we discuss an implementation of the Split&Merge architecture, that reduces video encoding times to fixed duration, independently of the input size of the video file, by using dynamic resource provisioning in the Cloud. 2010 IEEE.

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    Description

    Title : An Architecture for Distributed High Performance Video Processing in the Cloud
    Author(s) : Rafael Pereira, Marcello Azambuja, Karin Breitman, Markus Endler
    Abstract : Video processing applications are notably data intense, time, and resource consuming. Upfront infrastructure investment is usually high, specially when dealing with applications where time-to- market is a crucial requirement, e.g., breaking news and journalism. Such infrastructures are often inefficient, because due to demand variations, resources may end up idle a good portion of the time. In this paper, we propose the Split&Merge architecture for high performance video processing, a generalization of the MapReduce paradigm that rationalizes the use of resources by exploring on demand computing. To illustrate the approach, we discuss an implementation of the Split&Merge architecture, that reduces video encoding times to fixed duration, independently of the input size of the video file, by using dynamic resource provisioning in the Cloud. 2010 IEEE.
    Keywords : distributed architectures, cloud computing, departamento de informática, karin breitman, markus endler, service orientation, system architectures, video compression

    Subject : unspecified
    Area : Other
    Language : English
    Year : 2010

    Affiliations Dep. of Informatics, PUC-Rio, Brazil
    Journal : 2010 IEEE 3rd International Conference on Cloud Computing
    Publisher : IEEE
    Pages : 482 - 489
    Url : http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5557958
    Isbn : 978-1-4244-8207-8
    Doi : 10.1109/CLOUD.2010.73

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