MapReduce based experimental frame for parallel and distributed simulation using hadoop platform

Byeong Soo Kim, Sun Ju Lee, Tag Gon Kim, Hae Sang Song

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Simulation-based experiment of complex systems is a time consuming-job. Parallel and distributed simulation is one of the methods to reduce the simulation time. To simulate and analyze the system with this method, it is required to design a suitable experimental frame. Therefore, this paper proposes a MapReduce based experimental frame for the parallel and distributed simulation. Because Hadoop MapReduce is the most widely used parallel and distributed computing platform, we use it to design the experimental frame. In our work, the 'map' of MapReduce automatically generates and simulates the system, and the 'reduce' of MapReduce collects and analyzes the result. We can reuse the existing large scale Hadoop clusters without any modification of the platform, so it is easy to set-up and use the experimental frame. This paper presents an air defense simulation to show the usage and speed up with a 16-node Hadoop cluster. Proceedings 28th European Conference on Modelling and Simulation

Original languageEnglish
Title of host publicationProceedings - 28th European Conference on Modelling and Simulation, ECMS 2014
PublisherEuropean Council for Modelling and Simulation
Pages664-669
Number of pages6
ISBN (Print)9780956494481
DOIs
StatePublished - 2014
Event28th European Conference on Modelling and Simulation, ECMS 2014 - Brescia, Italy
Duration: 27 May 201430 May 2014

Publication series

NameProceedings - 28th European Conference on Modelling and Simulation, ECMS 2014

Conference

Conference28th European Conference on Modelling and Simulation, ECMS 2014
Country/TerritoryItaly
CityBrescia
Period27/05/1430/05/14

Keywords

  • Experimental frame
  • Hadoop
  • MapReduce
  • Parallel and distributed simulation
  • System analysis

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