A. Araujo, Cícero Garrozi, A. R. G. A. Leitão, M. Gouvêa
{"title":"Multicast routing using genetic algorithm seen as a permutation problem","authors":"A. Araujo, Cícero Garrozi, A. R. G. A. Leitão, M. Gouvêa","doi":"10.1109/AINA.2006.237","DOIUrl":null,"url":null,"abstract":"Classical approaches of multicast routing consider a tree path whose computational cost entails high use of resources such time and memory in the optimization process. This paper presents a genetic algorithm model applied to the multicast routing problem, in which no tree is built. The solution aims to maximize common paths in source-destinations routes and to minimize the route sizes. New options of fitness functions, variation and selection operators were proposed to increase the ability to generate feasible routes. The simulations were performed in two networks: the 33-node European GEANT WAN network to assess the capacity to find viable solutions and a 100-node network to test the capacity to handle larger networks. The results suggest promising performance for this approach.","PeriodicalId":185969,"journal":{"name":"20th International Conference on Advanced Information Networking and Applications - Volume 1 (AINA'06)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"20th International Conference on Advanced Information Networking and Applications - Volume 1 (AINA'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AINA.2006.237","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22
Abstract
Classical approaches of multicast routing consider a tree path whose computational cost entails high use of resources such time and memory in the optimization process. This paper presents a genetic algorithm model applied to the multicast routing problem, in which no tree is built. The solution aims to maximize common paths in source-destinations routes and to minimize the route sizes. New options of fitness functions, variation and selection operators were proposed to increase the ability to generate feasible routes. The simulations were performed in two networks: the 33-node European GEANT WAN network to assess the capacity to find viable solutions and a 100-node network to test the capacity to handle larger networks. The results suggest promising performance for this approach.