Routing and Scheduling in Time-Sensitive Networking by Evolutionary Algorithms.

IF 3.4 3区 医学 Q1 ENGINEERING, MULTIDISCIPLINARY
Zengkai Wang, Weizhi Liao, Xiaoyun Xia, Zijia Wang, Yaolong Duan
{"title":"Routing and Scheduling in Time-Sensitive Networking by Evolutionary Algorithms.","authors":"Zengkai Wang, Weizhi Liao, Xiaoyun Xia, Zijia Wang, Yaolong Duan","doi":"10.3390/biomimetics10050333","DOIUrl":null,"url":null,"abstract":"<p><p>Routing and scheduling in Time-Sensitive Networking (TSN) is an NP-hard problem. In this paper, we propose a novel routing and scheduling approach for TSN based on evolutionary algorithm. Specifically, we introduce a flow grouping method that leverages the greatest common divisor to optimize flow aggregation. On this basis, we develop a flow routing strategy that employs a genetic algorithm, where the evaluation function considers not only flow combinability but also path length and network load. By exploiting the non-combinable properties of flows, we effectively reduce the search space for the genetic algorithm. Furthermore, we design a scheduling method based on differential evolution algorithms tailored to TSN's requirements of zero jitter and no frame loss. We propose a gene coding method and rigorously prove its correctness, which significantly reduces the search space of the differential evolution algorithm. The experimental results demonstrate that our approach enables more flows to traverse along the shortest path compared to both k-shortest path methods and integer linear programming approaches, while achieving a faster execution time in large-scale scheduling scenarios.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 5","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109389/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomimetics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/biomimetics10050333","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Routing and scheduling in Time-Sensitive Networking (TSN) is an NP-hard problem. In this paper, we propose a novel routing and scheduling approach for TSN based on evolutionary algorithm. Specifically, we introduce a flow grouping method that leverages the greatest common divisor to optimize flow aggregation. On this basis, we develop a flow routing strategy that employs a genetic algorithm, where the evaluation function considers not only flow combinability but also path length and network load. By exploiting the non-combinable properties of flows, we effectively reduce the search space for the genetic algorithm. Furthermore, we design a scheduling method based on differential evolution algorithms tailored to TSN's requirements of zero jitter and no frame loss. We propose a gene coding method and rigorously prove its correctness, which significantly reduces the search space of the differential evolution algorithm. The experimental results demonstrate that our approach enables more flows to traverse along the shortest path compared to both k-shortest path methods and integer linear programming approaches, while achieving a faster execution time in large-scale scheduling scenarios.

基于进化算法的时间敏感网络中的路由和调度。
时间敏感网络(TSN)中的路由和调度是一个np难题。本文提出了一种基于进化算法的TSN路由调度方法。具体来说,我们引入了一种利用最大公约数优化流聚合的流分组方法。在此基础上,我们开发了一种采用遗传算法的流路由策略,其中评估函数不仅考虑了流的可组合性,而且考虑了路径长度和网络负载。利用流的不可组合性,有效地缩小了遗传算法的搜索空间。在此基础上,针对TSN的零抖动和无帧丢的要求,设计了一种基于差分进化算法的调度方法。我们提出了一种基因编码方法,并对其正确性进行了严格的证明,大大减少了差分进化算法的搜索空间。实验结果表明,与k-最短路径方法和整数线性规划方法相比,我们的方法可以使更多的流沿着最短路径遍历,同时在大规模调度场景中实现更快的执行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Biomimetics
Biomimetics Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
3.50
自引率
11.10%
发文量
189
审稿时长
11 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信