西安电子科技大学学报（自然科学版）2025，Vol.52Issue(6)：70-79,10.DOI:10.19665/j.issn1001-2400.20251003
改进直觉模糊软集的再生器部署方法
Regenerator placement based on improved fuzzy soft sets in EONs
摘要
Abstract
In elastic optical networks,regenerator deployment effectively alleviates the consistency constraints in spectrum allocation.It also reduces the request blocking probability.Studies show that the sparse deployment scheme has no significant performance difference compared to the full-node deployment scheme while it substantially reduces equipment costs.Therefore,node significance is assessed based on multi-dimensional network attributes.This paper proposes an improved intuitionistic fuzzy soft set ranking algorithm based on a hesitation factor.By combining the hesitation factor with the score function and the degree-accuracy function,the algorithm addresses the limitation of assessing solutions when the degree of membership is the same as that of non-membership.Additionally,a multi-criteria decision-making method is used to sort the results,overcoming the drawback of incomplete sorting due to equal evaluation values in single-criterion sorting.Simulation results demonstrate that compared to traditional intuitionistic fuzzy soft set-based ranking methods,when selecting a single node for regenerator placement,the request blocking rates in NSFNET and Cost-239 networks are reduced by 10.28％and 9.47％,respectively.As the number of selected nodes increases,the blocking rate gap further widens,providing an effective solution for optimized regenerator deployment in elastic optical networks.关键词
光网络/犹豫度因子/直觉模糊软集Key words
optical network/hesitation factor/fuzzy soft set分类
信息技术与安全科学引用本文复制引用
江婧,李兆坤,尚韬..改进直觉模糊软集的再生器部署方法[J].西安电子科技大学学报（自然科学版）,2025,52(6):70-79,10.基金项目
国家自然科学基金(62401428,62001286) （62401428,62001286）
陕西省自然科学基础研究计划(2024JC-YBQN-0714) （2024JC-YBQN-0714）
