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Reseach Article

A MR Simulator in Facilitating Cloud Computing

by R. Palson Kennedy, T. V. Gopal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 72 - Number 5
Year of Publication: 2013
Authors: R. Palson Kennedy, T. V. Gopal
10.5120/12494-9077

R. Palson Kennedy, T. V. Gopal . A MR Simulator in Facilitating Cloud Computing. International Journal of Computer Applications. 72, 5 ( June 2013), 43-49. DOI=10.5120/12494-9077

@article{ 10.5120/12494-9077,
author = { R. Palson Kennedy, T. V. Gopal },
title = { A MR Simulator in Facilitating Cloud Computing },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 72 },
number = { 5 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 43-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume72/number5/12494-9077/ },
doi = { 10.5120/12494-9077 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:37:10.703520+05:30
%A R. Palson Kennedy
%A T. V. Gopal
%T A MR Simulator in Facilitating Cloud Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 72
%N 5
%P 43-49
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

MapReduce is an enabling technology in support of Cloud Computing. Hadoop which is a mapReduce implementation has been widely used in developing MapReduce applications. This paper presents Hadoop simulator- HaSim, MapReduce simulator which builds on top of Hadoop. HaSim models large number of parameters that can affect the behaviors of MapReduce nodes, and thus it can be used to tune the performance of a MapReduce cluster. HaSim is validated with both benchmark results and user customized MapReduce applications.

References
  1. Apache Hadoop! Available at: http://hadoop. apache. org/ [Accessed Feb 2, 2013].
  2. Aarnio, T. (2010). Parallel Data Processing with Mapreduce. TKK T-110. 5190, Seminar on Internetworking, Available: http://www. cse. tkk. fi/en/publications/B/5/papers/Aarnio_final. pdf.
  3. Alham, N. K. , Li, M. , Hammoud, S. , Liu, Y. , and Ponraj, M. (2010). A distributed SVM for image annotation. In: Proceedings of the 7th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), YanTai, China
  4. He, B. , Fang, W. , Luo, Q. , Govindaraju, N. K. , and Wang, T. (2008). Mars: a MapReduce framework on graphics processors. In PACT '08: Proceedings of the 17th international conference on Parallel architectures and compilation techniques, 260–2698
  5. Pavlo, A. , Paulson, Madden, and S. , Stonebraker, M. (2009). A comparison of approaches to large-scale data analysis.
  6. Taura, K. , Kaneda, K. , Endo, T. , and Yonezawa, A. (2003). Phoenix: a parallel programming model for accommodating dynamically joining/leaving resources. SIGPLAN Not. , 38, 216–229. 7
  7. The Network Simulator - ns-2 Available at: http://www. isi. edu/nsnam/ns (Last accessed: 19-May-2013).
  8. Venner, J. (2012). Pro Hadoop (1st ed). New York: Springer.
  9. Wang, G. , Butt, A. R. , Pandey, P. , and Gupta, K. (2009). Using realistic simulation for performance analysis of mapreduce setups.
  10. Wang, G. , Butt, A. R. , Pandey, P. , and Gupta, K. (2011). A Simulation Approach to Evaluating Design Decisions in MapReduce Setups. In: Proceedings of the 17th Annual Meeting of the IEEE/ACM International Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS '11), London, UK.
Index Terms

Computer Science
Information Sciences

Keywords

MapReduce Hadoop framework Cloud Computing HaSim. Simulator Programming models