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dc.contributor.authorBarbecho Bautista, Pablo Andrés
dc.contributor.authorUrquiza Aguiar, Luis Felipe
dc.contributor.authorLemus Cárdenas, Leticia
dc.contributor.authorAguilar Igartua, Mónica
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Enginyeria Telemàtica
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica
dc.date.accessioned2020-10-19T18:44:09Z
dc.date.available2020-10-19T18:44:09Z
dc.date.issued2020-06-21
dc.identifier.citationBarbecho, P. [et al.]. Large-scale simulations manager tool for OMNeT ++: expediting simulations and post-processing analysis. "IEEE access", 21 Juny 2020, vol. 8, p. 159291-159306.
dc.identifier.issn2169-3536
dc.identifier.urihttp://hdl.handle.net/2117/330451
dc.description.abstractUsually, simulations are the first approach to evaluate wireless and mobile networks due to the difficulties involved in deploying real test scenarios. Working with simulations, testing, and validating the target network model often requires a large number of simulation runs. Consequently, there are a significant amount of outcomes to be analyzed to finally plot results. One of the most extensively used simulators for wireless and mobile networks is OMNeT++. This simulation environment provides useful tools to automate the execution of simulation campaigns, yet single-scenario simulations are also supported where the assignation of resources (i.e., CPUs) has to be declared manually. However, conducting a large number of simulations is still cumbersome and can be improved to make it easier, faster, and more comfortable to analyze. In this work, we propose a large-scale simulations framework called simulations manager for OMNeT ++ (SMO). SMO allows OMNeT++ users to quickly and easily execute large-scale network simulations, hiding the tedious process of conducting big simulation campaigns. Our framework automates simulations executions, resources assignment, and post-simulation data analysis through the use of Python’s wide established statistical analysis tools. Besides, our tool is flexible and easy to adapt to many different network scenarios. Our framework is accompanied by a command-line environment allowing a fast and easy manipulation that allows users to significantly reduce the total processing time to carry out large sets of simulations about 25% of the original time. Our code and its documentation are publicly available at GitHub and on our website.
dc.description.sponsorshipThis work was supported by the Spanish Government through the Research Project sMArt Grid Using Open Source Intelligence (MAGOS) under Grant TEC2017-84197-C4-3-R. The work of Pablo Andrés Barbecho Bautista was supported by a grant from the Secretaría Nacional de Educación Superior, Ciencia y Tecnología (SENESCYT). The work of Leticia Lemus CÁrdenas was supported by a Ph.D. grant from the Academic Coordination of the University of Guadalajara, Mexico.
dc.format.extent16 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Comunicacions mòbils
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
dc.subject.lcshMobile communication systems
dc.subject.lcshWireless communication systems
dc.subject.otherLarge-scale simulations
dc.subject.otherOMNeT++
dc.subject.otherResults post-processing
dc.titleLarge-scale simulations manager tool for OMNeT ++: expediting simulations and post-processing analysis
dc.typeArticle
dc.subject.lemacComunicacions mòbils, Sistemes de
dc.subject.lemacComunicació sense fil, Sistemes de
dc.contributor.groupUniversitat Politècnica de Catalunya. SISCOM - Smart Services for Information Systems and Communication Networks
dc.identifier.doi10.1109/ACCESS.2020.3020745
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/abstract/document/9181563
dc.rights.accessOpen Access
local.identifier.drac28794489
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/2PE/TEC2017-84197-C4-3-R
local.citation.authorBarbecho, P.; Urquiza, L.; Lemus, L.; Aguilar Igartua, M.
local.citation.publicationNameIEEE access
local.citation.volume8
local.citation.startingPage159291
local.citation.endingPage159306


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