A hadoop-based multimedia transcoding system for processing social media in the PaaS platform of SMCCSE

Myoungjin Kim, Seungho Han, Yun Cui, Hanku Lee, Chang-Sung Jeong

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Previously, we described a social media cloud computing service environment (SMCCSE). This SMCCSE supports the development of social networking services (SNSs) that include audio, image, and video formats. A social media cloud computing PaaS platform, a core component in a SMCCSE, processes large amounts of social media in a parallel and distributed manner for supporting a reliable SNS. Here, we propose a Hadoop-based multimedia system for image and video transcoding processing, necessary functions of our PaaS platform. Our system consists of two modules, including an image transcoding module and a video transcoding module. We also design and implement the system by using a MapReduce framework running on a Hadoop Distributed File System (HDFS) and the media processing libraries Xuggler and JAI. In this way, our system exponentially reduces the encoding time for transcoding large amounts of image and video files into specific formats depending on user-requested options (such as resolution, bit rate, and frame rate). In order to evaluate system performance, we measure the total image and video transcoding time for image and video data sets, respectively, under various experimental conditions. In addition, we compare the video transcoding performance of our cloud-based approach with that of the traditional frame-level parallel processing-based approach. Based on experiments performed on a 28-node cluster, the proposed Hadoop-based multimedia transcoding system delivers excellent speed and quality.

Original languageEnglish
Pages (from-to)2827-2848
Number of pages22
JournalKSII Transactions on Internet and Information Systems
Volume6
Issue number11
Publication statusPublished - 2012 Nov 30

Fingerprint

Multimedia systems
Cloud computing
Processing
Experiments

Keywords

  • Cloud computing
  • Hadoop
  • Mapreduce
  • Multimedia transcoding
  • Paas

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

Cite this

A hadoop-based multimedia transcoding system for processing social media in the PaaS platform of SMCCSE. / Kim, Myoungjin; Han, Seungho; Cui, Yun; Lee, Hanku; Jeong, Chang-Sung.

In: KSII Transactions on Internet and Information Systems, Vol. 6, No. 11, 30.11.2012, p. 2827-2848.

Research output: Contribution to journalArticle

@article{0c6a228145ba44599479dcfac64a1e01,
title = "A hadoop-based multimedia transcoding system for processing social media in the PaaS platform of SMCCSE",
abstract = "Previously, we described a social media cloud computing service environment (SMCCSE). This SMCCSE supports the development of social networking services (SNSs) that include audio, image, and video formats. A social media cloud computing PaaS platform, a core component in a SMCCSE, processes large amounts of social media in a parallel and distributed manner for supporting a reliable SNS. Here, we propose a Hadoop-based multimedia system for image and video transcoding processing, necessary functions of our PaaS platform. Our system consists of two modules, including an image transcoding module and a video transcoding module. We also design and implement the system by using a MapReduce framework running on a Hadoop Distributed File System (HDFS) and the media processing libraries Xuggler and JAI. In this way, our system exponentially reduces the encoding time for transcoding large amounts of image and video files into specific formats depending on user-requested options (such as resolution, bit rate, and frame rate). In order to evaluate system performance, we measure the total image and video transcoding time for image and video data sets, respectively, under various experimental conditions. In addition, we compare the video transcoding performance of our cloud-based approach with that of the traditional frame-level parallel processing-based approach. Based on experiments performed on a 28-node cluster, the proposed Hadoop-based multimedia transcoding system delivers excellent speed and quality.",
keywords = "Cloud computing, Hadoop, Mapreduce, Multimedia transcoding, Paas",
author = "Myoungjin Kim and Seungho Han and Yun Cui and Hanku Lee and Chang-Sung Jeong",
year = "2012",
month = "11",
day = "30",
language = "English",
volume = "6",
pages = "2827--2848",
journal = "KSII Transactions on Internet and Information Systems",
issn = "1976-7277",
publisher = "Korea Society of Internet Information",
number = "11",

}

TY - JOUR

T1 - A hadoop-based multimedia transcoding system for processing social media in the PaaS platform of SMCCSE

AU - Kim, Myoungjin

AU - Han, Seungho

AU - Cui, Yun

AU - Lee, Hanku

AU - Jeong, Chang-Sung

PY - 2012/11/30

Y1 - 2012/11/30

N2 - Previously, we described a social media cloud computing service environment (SMCCSE). This SMCCSE supports the development of social networking services (SNSs) that include audio, image, and video formats. A social media cloud computing PaaS platform, a core component in a SMCCSE, processes large amounts of social media in a parallel and distributed manner for supporting a reliable SNS. Here, we propose a Hadoop-based multimedia system for image and video transcoding processing, necessary functions of our PaaS platform. Our system consists of two modules, including an image transcoding module and a video transcoding module. We also design and implement the system by using a MapReduce framework running on a Hadoop Distributed File System (HDFS) and the media processing libraries Xuggler and JAI. In this way, our system exponentially reduces the encoding time for transcoding large amounts of image and video files into specific formats depending on user-requested options (such as resolution, bit rate, and frame rate). In order to evaluate system performance, we measure the total image and video transcoding time for image and video data sets, respectively, under various experimental conditions. In addition, we compare the video transcoding performance of our cloud-based approach with that of the traditional frame-level parallel processing-based approach. Based on experiments performed on a 28-node cluster, the proposed Hadoop-based multimedia transcoding system delivers excellent speed and quality.

AB - Previously, we described a social media cloud computing service environment (SMCCSE). This SMCCSE supports the development of social networking services (SNSs) that include audio, image, and video formats. A social media cloud computing PaaS platform, a core component in a SMCCSE, processes large amounts of social media in a parallel and distributed manner for supporting a reliable SNS. Here, we propose a Hadoop-based multimedia system for image and video transcoding processing, necessary functions of our PaaS platform. Our system consists of two modules, including an image transcoding module and a video transcoding module. We also design and implement the system by using a MapReduce framework running on a Hadoop Distributed File System (HDFS) and the media processing libraries Xuggler and JAI. In this way, our system exponentially reduces the encoding time for transcoding large amounts of image and video files into specific formats depending on user-requested options (such as resolution, bit rate, and frame rate). In order to evaluate system performance, we measure the total image and video transcoding time for image and video data sets, respectively, under various experimental conditions. In addition, we compare the video transcoding performance of our cloud-based approach with that of the traditional frame-level parallel processing-based approach. Based on experiments performed on a 28-node cluster, the proposed Hadoop-based multimedia transcoding system delivers excellent speed and quality.

KW - Cloud computing

KW - Hadoop

KW - Mapreduce

KW - Multimedia transcoding

KW - Paas

UR - http://www.scopus.com/inward/record.url?scp=84870706422&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84870706422&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:84870706422

VL - 6

SP - 2827

EP - 2848

JO - KSII Transactions on Internet and Information Systems

JF - KSII Transactions on Internet and Information Systems

SN - 1976-7277

IS - 11

ER -