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A Novel Technique for Parallelization of Genetic Algorithm using Hadoop

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Author(s): Ms. Kanchan Sharadchandra Rahate (Khedikar)#1 Prof. L.M.R.J. Lobo

Journal: International Journal of Engineering Trends and Technology
ISSN 2231-5381

Volume: 4;
Issue: 8;
Start page: 3328;
Date: 2013;
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Keywords: Hadoop | HDFS | MapReduce | PGA | OlexGA.

ABSTRACT
Document categorization is used in education, government sectors, art, industry etc. Categorizing a document to enable immediate finding of it in the future motivated the concept of Classification involving Document categorization. Manual document classification involves a lot of effort and is time consuming. The basic idea implemented in this paper speeds up processing and reduces manual intervention, by atomizing this categorization. This idea is an edge over the existing classification systems. The implementation of the system basically involves getting into to parallelize Genetic Algorithm (GA) thus improving the processing speed. The useof Hadoop MapReduce and HDFS (Hadoop Distributed File System) framework helps to store big data and speeds up the calculations involved in the computation of genetic algorithm. The motivation of this work has reason from mapreduce fare well in terms of scalability, fault tolerance, and ease-of-use. This is adjoined by hadoop being an open-source and hadoop being written in Java.
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