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A Review: Distributed Video Transcoding using Big Data & Hadoop

Author(s):

Mr. Bhagate Akshay , DR. J. J. MAGDUM COLLEGE OF ENGINEERING, JAYSINGPUR; Mr. Tamhankar Aditya, DR. J. J. MAGDUM COLLEGE OF ENGINEERING, JAYSINGPUR; Mr. Bedkyale Sourabh, DR. J. J. MAGDUM COLLEGE OF ENGINEERING, JAYSINGPUR; Mr. Hattekar Mayur, DR. J. J. MAGDUM COLLEGE OF ENGINEERING, JAYSINGPUR; Mr. Mulla Tahseen, DR. J. J. MAGDUM COLLEGE OF ENGINEERING, JAYSINGPUR

Keywords:

Big Data & Hadoop, video transcoding system

Abstract

In this paper proposed a Hadoop-based Distributed Video Transcoding System that transcodes a large number of video data sets into mp4 video formats, several challenges are identified with respect to the video bearing, such as the different video formats, and compatibility with different terminal devices? The video transcoding system (VTS) is useful to achieve these challenges. This paper introduces a Hadoop based, video transcoding system to fulfill the vision of relevance thousands of HD video streams in the any Network, with using a different parameters. This paper obtains mainly information about Video Transcoding Using Big data & Hadoop. Apply a Hadoop Distributed File System (HDFS) and a MapReduce framework to the system. In this study, we measure the total transcoding time for various values of MapReduce tuning parameters: block replication factor and Hadoop Distributed File System block size. Thus, we determine the optimal values of the parameters affecting transcoding performance.

Other Details

Paper ID: IJSRDV5I20811
Published in: Volume : 5, Issue : 2
Publication Date: 01/05/2017
Page(s): 2058-2061

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