NDLI: Towards a framework for large-scale multimedia data storage and processing on Hadoop platform

Content Provider	Springer Nature Link
Author	Lai, Wei Kuang Chen, Yi Uan Wu, Tin Yu Obaidat, Mohammad S.
Copyright Year	2013
Abstract	Cloud computing techniques take the form of distributed computing by utilizing multiple computers to execute computing simultaneously on the service side. To process the increasing quantity of multimedia data, numerous large-scale multimedia data storage computing techniques in the cloud computing have been developed. Of all the techniques, Hadoop plays a key role in the cloud computing. Hadoop, a computing cluster formed by low-priced hardware, can conduct the parallel computing of petabytes of multimedia data. Hadoop features high-reliability, high-efficiency, and high-scalability. The numerous large-scale multimedia data computing techniques include not only the key core techniques, Hadoop and MapReduce, but also the data collection techniques, such as File Transfer Protocol and Flume. In addition, distributed system configuration allocation, automatic installation, and monitoring platform building and management techniques are all included. As a result, only with the integration of all the techniques, a reliable large-scale multimedia data platform can be offered. In this paper, we introduce how cloud computing can make a breakthrough by proposing a multimedia social network dataset on Hadoop platform and implementing a prototype version. Detailed specifications and design issues are discussed as well. An important finding of this article is that we can save more time if we conduct the multimedia social networking analysis using Cloud Hadoop Platform rather than using a single computer. The advantages of cloud computing over the traditional data processing practices are fully demonstrated in this article. The applicable framework designs and the tools available for the large-scale data processing are also proposed. We show the experimental multimedia data including data sizes and processing time.
Starting Page	488
Ending Page	507
Page Count	20
File Format	PDF
ISSN	09208542
Journal	The Journal of Supercomputing
Volume Number	68
Issue Number	1
e-ISSN	15730484
Language	English
Publisher	Springer US
Publisher Date	2013-12-05
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Cloud computing Hadoop MapReduce BigTable High performance computing Programming Languages, Compilers, Interpreters Processor Architectures Computer Science
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Information Systems Hardware and Architecture Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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