DocumentCode
262311
Title
A Hadoop-Based Output Analyzer for Large-Scale Simulation Data
Author
Kangsun Lee ; Joonho Park
Author_Institution
Dept. of Comput. Eng., MyongJi Univ., Yongin, South Korea
fYear
2014
fDate
3-5 Dec. 2014
Firstpage
197
Lastpage
200
Abstract
As modern simulations involve large inputs and outputs over the network, there is an increasing need to store, manage and analyze the massive datasets, efficiently. In this paper, we present ARLS (After action Reviewer for Large-Scale simulation data), a Hadoop-based output analysis tool for large-scale simulation datasets. ARLS clusters distributed storages using Hadoop and analyzes the large-scale datasets using MapReduce. According to the experiments we have conducted, ARLS improved data processing time significantly comparing to the traditional output analysis tools.
Keywords
data handling; parallel processing; ARLS; Hadoop-based output analysis tool; Hadoop-based output analyzer; MapReduce; after action reviewer for large-scale simulation data; Analytical models; Atmospheric modeling; Cloud computing; Computational modeling; Computers; Data models; Educational institutions; Cloud Storages; Large-Scale Data Analysis; Modeling and Simulation for Large Scale Data; Output Analyzer;
fLanguage
English
Publisher
ieee
Conference_Titel
Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on
Conference_Location
Sydney, NSW
Type
conf
DOI
10.1109/BDCloud.2014.61
Filename
7034786
Link To Document