{"title":"Design of a Heuristic Topology Generation Algorithm in Multi-Domain Optical Networks","authors":"Lei Wang, Hua Feng, Li Lin, Li Du","doi":"10.4236/CN.2018.103006","DOIUrl":null,"url":null,"abstract":"Designing an excellent original topology not only improves the accuracy of routing, but also improves the restoring rate of failure. In this paper, we propose a new heuristic topology generation algorithm—GA-PODCC (Genetic Algorithm based on the Pareoto Optimality of Delay, Configuration and Consumption), which utilizes a genetic algorithm to optimize the link delay and resource configuration/consumption. The novelty lies in designing the two stages of genetic operation: The first stage is to pick the best population by means of the crossover, mutation, and selection operation; The second stage is to select an excellent individual from the best population. The simulation results show that, using the same number of nodes, GA-PODCC algorithm improves the balance of all the three optimization objectives, maintaining a low level of distortion in topology aggregation.","PeriodicalId":91826,"journal":{"name":"... IEEE Conference on Communications and Network Security. IEEE Conference on Communications and Network Security","volume":"130 1","pages":"65-77"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"... IEEE Conference on Communications and Network Security. IEEE Conference on Communications and Network Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4236/CN.2018.103006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Designing an excellent original topology not only improves the accuracy of routing, but also improves the restoring rate of failure. In this paper, we propose a new heuristic topology generation algorithm—GA-PODCC (Genetic Algorithm based on the Pareoto Optimality of Delay, Configuration and Consumption), which utilizes a genetic algorithm to optimize the link delay and resource configuration/consumption. The novelty lies in designing the two stages of genetic operation: The first stage is to pick the best population by means of the crossover, mutation, and selection operation; The second stage is to select an excellent individual from the best population. The simulation results show that, using the same number of nodes, GA-PODCC algorithm improves the balance of all the three optimization objectives, maintaining a low level of distortion in topology aggregation.
设计一个优秀的原始拓扑不仅可以提高路由的精度,而且可以提高故障的恢复率。本文提出了一种新的启发式拓扑生成算法ga - podcc (Genetic Algorithm based on the Pareoto Optimality of Delay, Configuration and Consumption),该算法利用遗传算法对链路延迟和资源配置/消耗进行优化。其新颖之处在于设计了两个阶段的遗传操作:第一阶段是通过交叉、突变和选择操作来挑选最优群体;第二阶段是从最优群体中选择一个优秀的个体。仿真结果表明,在节点数相同的情况下,GA-PODCC算法提高了三个优化目标的均衡性,保持了较低的拓扑聚合失真水平。