Parallel and Distributed Framework for Standalone Monte Carlo Simulation using MapReduce

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 270
  • Download : 285
This paper deals with an efficient and robust parallel and distributed simulation framework for standalone Monte Carlo simulation based on a MapReduce computing framework. The Monte Carlo simulation method is inherently computing-intensive and requires many replicated simulation runs to get meaningful statistical results. Thus, it is important to reduce total simulation time by exploiting hardware and/or software as well as to reuse existing standalone simulation programs with little modification for the replicated simulations. To cope with this situation, we propose a general framework that turns a stand-alone Monte Carlo simulator into a chain of MapReduce jobs in order to run the simulation on a MapReduce framework such as Hadoop. A case study of an air defense simulation on 16-node Hadoop cluster illustrates that the proposed framework is feasible and fully utilizes the merit of the parallel and distributed computing environment.
Publisher
INDIAN J SCIENCE & TECHNOLOGY
Issue Date
2015-10
Language
English
Citation

INDIAN JOURNAL OF SCIENCE AND TECHNOLOGY, v.8, no.25

ISSN
0974-6846
DOI
10.17485/ijst/2015/v8i25/80004
URI
http://hdl.handle.net/10203/203738
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
80004-136454-2-PB.pdf(1.3 MB)Download

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0