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An Architecture for Distributed High Performance Video Processing in the Cloud

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4 Author(s)
Pereira, R. ; WebMedia Globo.com, Rio de Janeiro, Brazil ; Azambuja, M. ; Breitman, K. ; Endler, M.

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.

Published in:

Cloud Computing (CLOUD), 2010 IEEE 3rd International Conference on

Date of Conference:

5-10 July 2010