A survey on parallel clustering technique for big data framework

Mallik, Moksud Alam and Zulkurnain, Nurul Fariza and Jamil Ahmed, S. K. and Nizamuddin, Mohammed Khaja (2021) A survey on parallel clustering technique for big data framework. In: 2nd Global Conference on Artificial Intelligence and Applications (GCAIA 2021), 8-10 September 2021, Jaipur, India.

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Abstract

Clustering techniques for little data sets have built excellent develops and numerous successful clustering techniques have been designed. Nevertheless, these techniques are not giving adequate results when trading with extensive data sets. The most important problems are excessive computational difficulty and lengthy evaluating time, which is not acceptable for real time context. It is very prime to process this enormous information on time. Consequently, the investigation on clustering techniques for extensive data sets has begun to be one of the major jobs in the area of big data framework. This survey centers on a sharp investigation of various parallel clustering strategies featuring the qualities of large information. A short outline of various parallel clustering techniques which are based on Map Reduce evaluating technology, the clustering techniques based on Spark evaluating technology and the clustering techniques based on Storm evaluating technology.

Item Type:	Conference or Workshop Item (Plenary Papers)
Uncontrolled Keywords:	Clustering, Big Data, Parallel Processing
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User:	DR Nurul Fariza Zulkurnain
Date Deposited:	29 Jul 2022 11:59
Last Modified:	29 Jul 2022 11:59
URI:	http://irep.iium.edu.my/id/eprint/98962

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