DocumentCode :
3729179
Title :
An optimized cloud based big data processing mechanism using Self-Organizing Map in Hadoop environments
Author :
Girish Neelakanta Iyer;Salaja Silas;Ganesh Iyer
Author_Institution :
Department of Computer Science and Engineering, Aryanet Institute of Technology, Palakkad, India
fYear :
2015
Firstpage :
244
Lastpage :
246
Abstract :
Large scale searching problems such as searching for a particular tag in a set of web pages are always challenging. Distributed implementation of such searching algorithms are used in different distributed systems that includes Grid, Hadoop etc. In general, hadoop framework uses the Hadoop Distributed File System (HDFS) for all kinds of data processing. But the efficiency regarding the time in a distributed environment for data processing without any optimized algorithm is comparatively low. In this work, these problems are addressed. Searching using MapReduce paradigm is considered for implementing proposed scheme in the popular Open Source Cloud computing platform Hadoop and a neural network optimization algorithm named Self Organizing Maps (SOM). The processing speed got increased as the number of nodes in the Hadoop environment increases.
Keywords :
"Distributed databases","Big data","Clustering algorithms","Self-organizing feature maps","Computational modeling","Cloud computing"
Publisher :
ieee
Conference_Titel :
Green Computing and Internet of Things (ICGCIoT), 2015 International Conference on
Type :
conf
DOI :
10.1109/ICGCIoT.2015.7380466
Filename :
7380466
Link To Document :
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