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A Review on Genetic Algorithm Practice in Hadoop MapReduce


Author(s):

Mrs. C.Sunitha , Sri Krishna Arts and Science College Kuniamuthur , Coimbatore; Ms. I.Jeevitha, Sri Krishna Arts and Science College Kuniamuthur , Coimbatore

Keywords:

Genetic Algorithm, Hadoop, Map Reduce, Parallel GAs

Abstract:

In recent days generating data transfer become faster than ever. Need to maintain huge datasets, systems are increasingly interconnected. The Big data is the collection of large data sets, like billions of billion data stored and accessed at one place that cannot be processed by using traditional computing techniques. The Big data at whole will survey with several tools, techniques and framework. The ubiquitous key to the big data access is Hadoop. Hadoop is a framework used for processing large amount of data in parallel. Hadoop provide the reliability in storing the data and efficient processing system. Two main gears of Hadoop are the HDFS (Hadoop Distributed File System) and Map Reducing (for processing). Hadoop cluster is a vital element, where it folds all the datasets. It is constructed by nodes i.e. server, most are slave nodes, few are master nodes which are interconnected. Map reducing is a processing model; accomplishing the task by using Map and Reduce method. Genetic algorithm (GA) is a dominant metaheuristic search technique, which is used to solve many real world applications. The GAs find the optimal solution with reasonable time, that can be executed in parallel. Though implementing GAs in Hadoop is not easy, finding the solution which could survey for the fittest is superior.


Other Details:

Manuscript Id :IJSTEV2I5073
Published in :Volume : 2, Issue : 5
Publication Date: 01/12/2015
Page(s): 150-155
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