{"title":"WDM光网络上的路由和波长分配:moaco与经典方法的比较","authors":"A. Arteta, B. Barán, D. Pinto","doi":"10.1145/1384117.1384126","DOIUrl":null,"url":null,"abstract":"The increasing demand of bandwidth has found an answer in Optical Transport Networks (OTN). To take advantage of the different resources that OTNs offer, several parameters need to be optimized to obtain good performance. Therefore, this work studies the Routing and Wavelength Assignment (RWA) problem in a multiobjective context. MultiObjective Ant Colony Optimization (MOACO) algorithms are implemented to simultaneously optimize the hop count and number of wavelength conversion for a set of unicast demands, considering wavelength conflicts. This way, a set of optimal solutions, known as Pareto Set, is calculated in one run of the proposed algorithm, without a priori restrictions on some objective. The proposed MOACO algorithms were compared to classical RWA heuristics using several performance metrics. Although, there is not a clear superiority, simulation results indicate that considering most of the performance metrics, MOACO algorithms obtain promising results when compared to the classical heuristics.","PeriodicalId":415618,"journal":{"name":"International Latin American Networking Conference","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Routing and wavelength assignment over WDM optical networks: a comparison between MOACOs and classical approaches\",\"authors\":\"A. Arteta, B. Barán, D. Pinto\",\"doi\":\"10.1145/1384117.1384126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The increasing demand of bandwidth has found an answer in Optical Transport Networks (OTN). To take advantage of the different resources that OTNs offer, several parameters need to be optimized to obtain good performance. Therefore, this work studies the Routing and Wavelength Assignment (RWA) problem in a multiobjective context. MultiObjective Ant Colony Optimization (MOACO) algorithms are implemented to simultaneously optimize the hop count and number of wavelength conversion for a set of unicast demands, considering wavelength conflicts. This way, a set of optimal solutions, known as Pareto Set, is calculated in one run of the proposed algorithm, without a priori restrictions on some objective. The proposed MOACO algorithms were compared to classical RWA heuristics using several performance metrics. Although, there is not a clear superiority, simulation results indicate that considering most of the performance metrics, MOACO algorithms obtain promising results when compared to the classical heuristics.\",\"PeriodicalId\":415618,\"journal\":{\"name\":\"International Latin American Networking Conference\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Latin American Networking Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1384117.1384126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Latin American Networking Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1384117.1384126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Routing and wavelength assignment over WDM optical networks: a comparison between MOACOs and classical approaches
The increasing demand of bandwidth has found an answer in Optical Transport Networks (OTN). To take advantage of the different resources that OTNs offer, several parameters need to be optimized to obtain good performance. Therefore, this work studies the Routing and Wavelength Assignment (RWA) problem in a multiobjective context. MultiObjective Ant Colony Optimization (MOACO) algorithms are implemented to simultaneously optimize the hop count and number of wavelength conversion for a set of unicast demands, considering wavelength conflicts. This way, a set of optimal solutions, known as Pareto Set, is calculated in one run of the proposed algorithm, without a priori restrictions on some objective. The proposed MOACO algorithms were compared to classical RWA heuristics using several performance metrics. Although, there is not a clear superiority, simulation results indicate that considering most of the performance metrics, MOACO algorithms obtain promising results when compared to the classical heuristics.