@inproceedings{df19ea02414645a29b00ba1e2041115a,
title = "Performance analysis of MapReduce-based distributed systems for iterative data processing applications",
abstract = "Recently, research on big data has been actively made because big data are generated in various scientific applications, such as biology and astronomy. Therefore, distributed data processing techniques have been studied to manage the big data in large number servers. Meanwhile, some scientific applications like genome data analysis require loop control in analyzing big data using a MapReduce framework. In this paper, we first describe the existing MapReduce-based distributed systems which support iterative data processing. In addition, we do the performance analysis of the existing distributed systems in terms of execution time for various scientific applications which require iterative data processing. Finally, based on the performance analysis, we discuss some requirements for a new MapReduce-based distributed system which supports iterative data processing efficiently.",
keywords = "Big data, iterative data processing, MapReduce-based distributed systems",
author = "Min Yoon and Kim, \{Hyeong Il\} and Choi, \{Dong Hoon\} and Heeseung Jo and Chang, \{Jae Woo\}",
year = "2014",
doi = "10.1007/978-3-642-40675-1\_45",
language = "English",
isbn = "9783642406744",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "293--299",
booktitle = "Mobile, Ubiquitous, and Intelligent Computing, MUSIC 2013",
note = "4th International Conference on Mobile, Ubiquitous, and Intelligent Computing, MUSIC 2013 ; Conference date: 04-09-2013 Through 06-09-2013",
}