多域光网络中启发式拓扑生成算法的设计

Lei Wang, Hua Feng, Li Lin, Li Du
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引用次数: 2

摘要

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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of a Heuristic Topology Generation Algorithm in Multi-Domain Optical Networks
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.
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