{"title":"Layered architectural approach for distributed simulation systems: The SimArch case","authors":"Daniele Gianni","doi":"10.1201/b17902-11","DOIUrl":null,"url":null,"abstract":"As soon as the first computers became available, scientists in the most varied disciplines started using them to run mathematical models to predict the behavior and the performance of physical systems. As computational capabilities evolved, simulation became an essential tool in the support of activities in science and systems engineering. Models grew in size and in complexity, and became widely accessible with the advent of free, opensource simulators. In spite of significant, positive advances, the general area of simulation has witnessed growing concerns with the fidelity of results published in research literature. The so-called “crisis of credibility” in the field of network simulation is emblematic of this trend. Through years of investigation, scholars have identified a multiplicity of issues that have conspired against the scientific rigor of network simulation results. The simulation community learned that many of the failures in simulation studies arise from the complexity of the simulation workflow, which introduces several","PeriodicalId":395709,"journal":{"name":"Modeling and Simulation-Based Systems Engineering Handbook","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Modeling and Simulation-Based Systems Engineering Handbook","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1201/b17902-11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
As soon as the first computers became available, scientists in the most varied disciplines started using them to run mathematical models to predict the behavior and the performance of physical systems. As computational capabilities evolved, simulation became an essential tool in the support of activities in science and systems engineering. Models grew in size and in complexity, and became widely accessible with the advent of free, opensource simulators. In spite of significant, positive advances, the general area of simulation has witnessed growing concerns with the fidelity of results published in research literature. The so-called “crisis of credibility” in the field of network simulation is emblematic of this trend. Through years of investigation, scholars have identified a multiplicity of issues that have conspired against the scientific rigor of network simulation results. The simulation community learned that many of the failures in simulation studies arise from the complexity of the simulation workflow, which introduces several