Indian Journal of Science and Technology
DOI: 10.17485/ijst/2015/v8i25/80004
Year: 2015, Volume: 8, Issue: 25, Pages: 1-8
Original Article
Byeong Soo Kim1 , Tag Gon Kim1 and Hae Sang Song2 *
1 Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Republic of Korea;
2 Department of Computer Engineering, Seowon University, Republic of Korea; [email protected]
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.
Keywords: MapReduce, Monte Carlo Simulation, Parallel and Distributed Simulation, System Analysis
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