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
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;
Conference_Titel :
Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on
Conference_Location :
Sydney, NSW
DOI :
10.1109/BDCloud.2014.61