Matthieu Mastio, Mahdi Zargayouna, G. Scémama, O. Rana
{"title":"Patterns to distribute mobility simulations","authors":"Matthieu Mastio, Mahdi Zargayouna, G. Scémama, O. Rana","doi":"10.1109/AICCSA.2016.7945676","DOIUrl":null,"url":null,"abstract":"Travelers mobility simulation is a powerful tool to test strategies in a virtual environment, without impacting the quality of the real traffic network. However, existing mobility multiagent and micro-simulations can only consider a sample of the real volumes of travelers, especially for big regions. With distributed simulations, it would be easier to analyze and predict the status of nowadays networks. This kind of simulations requires big computational power and methods to split the simulation between several machines. This work describes how to achieve such a distribution in a microscopic simulation context, and compare our results with a previous work on macroscopic simulation.","PeriodicalId":448329,"journal":{"name":"2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICCSA.2016.7945676","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Travelers mobility simulation is a powerful tool to test strategies in a virtual environment, without impacting the quality of the real traffic network. However, existing mobility multiagent and micro-simulations can only consider a sample of the real volumes of travelers, especially for big regions. With distributed simulations, it would be easier to analyze and predict the status of nowadays networks. This kind of simulations requires big computational power and methods to split the simulation between several machines. This work describes how to achieve such a distribution in a microscopic simulation context, and compare our results with a previous work on macroscopic simulation.