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A Distributed Video Management Cloud Platform Using Hadoop
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DOI：10.1109/ACCESS.2015.2507788.png)
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Abstract
En 中文
Due to complexities of big video data management, such as massive processing of large amount of video data to do a video summary, it is challenging to effectively and efficiently store and process these video data in a user friendly way. Based on the parallel processing and flexible storage capabilities of cloud computing, in this paper, we propose a practical massive video management platform using Hadoop, which can achieve a fast video processing (such as video summary, encoding, and decoding) using MapReduce, with good usability, performance, and availability. Red5 streaming media server is used to get video stream from Hadoop distributed file system, and Flex is used to play video in browsers. A user-friendly interface is designed for managing the whole platform in a browser server style using J2EE. In addition, we show our experiences on how to fine-tune the Hadoop to get optimized performance for different video processing tasks. The evaluations show that the proposed platform can satisfy the requirements of massive video data management.
Keywords:
Hadoop
J2EE
video processing
MapReduce
video management
Journal
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3.6
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