遗传算法解决波分复用全光网络中路由和波长分配问题

Ravi Sankar Barpanda, A. K. Turuk, B. Sahoo, B. Majhi
{"title":"遗传算法解决波分复用全光网络中路由和波长分配问题","authors":"Ravi Sankar Barpanda, A. K. Turuk, B. Sahoo, B. Majhi","doi":"10.1109/COMSNETS.2011.5716507","DOIUrl":null,"url":null,"abstract":"Routing and Wavelength Assignment (RWA) problem in Wavelength Division Multiplexed (WDM) optical networks assumes assigning the routes and wavelengths to be used to create the lightpaths on behalf of the connection requests. The RWA problem belongs to the class of combinatorial optimization problems. The optimal solution to the RWA problem is found to be NP-hard and thus suited to heuristic approaches. We formulate an Integer Linear Programming (ILP) problem to model the RWA problem as an optimization problem and solve the formulated ILP using Genetic Algorithm (GA) heuristic to obtain a near optimal solution in polynomial time. Our primary optimization objective is the establishment of connection requests with minimum congestion among the individuals. The secondary targets are to minimize the hop count, route length, the number of fiber links utilized to honor all the lightpath requests. The GA based heuristic approach is simulated on ARPANET (Advanced Research Project Agency NETwork) and the results obtained for the multi objective GA are compared with the single objective GA. The results show that multi objective GA performs better than single objective GA while optimizing different network parameters.","PeriodicalId":302678,"journal":{"name":"2011 Third International Conference on Communication Systems and Networks (COMSNETS 2011)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Genetic Algorithm techniques to solve Routing and Wavelength Assignment problem in Wavelength Division Multiplexing all-optical networks\",\"authors\":\"Ravi Sankar Barpanda, A. K. Turuk, B. Sahoo, B. Majhi\",\"doi\":\"10.1109/COMSNETS.2011.5716507\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Routing and Wavelength Assignment (RWA) problem in Wavelength Division Multiplexed (WDM) optical networks assumes assigning the routes and wavelengths to be used to create the lightpaths on behalf of the connection requests. The RWA problem belongs to the class of combinatorial optimization problems. The optimal solution to the RWA problem is found to be NP-hard and thus suited to heuristic approaches. We formulate an Integer Linear Programming (ILP) problem to model the RWA problem as an optimization problem and solve the formulated ILP using Genetic Algorithm (GA) heuristic to obtain a near optimal solution in polynomial time. Our primary optimization objective is the establishment of connection requests with minimum congestion among the individuals. The secondary targets are to minimize the hop count, route length, the number of fiber links utilized to honor all the lightpath requests. The GA based heuristic approach is simulated on ARPANET (Advanced Research Project Agency NETwork) and the results obtained for the multi objective GA are compared with the single objective GA. The results show that multi objective GA performs better than single objective GA while optimizing different network parameters.\",\"PeriodicalId\":302678,\"journal\":{\"name\":\"2011 Third International Conference on Communication Systems and Networks (COMSNETS 2011)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-02-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Third International Conference on Communication Systems and Networks (COMSNETS 2011)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMSNETS.2011.5716507\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Third International Conference on Communication Systems and Networks (COMSNETS 2011)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMSNETS.2011.5716507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16

摘要

波分复用(WDM)光网络中的路由和波长分配(RWA)问题假定为连接请求分配用于创建光路的路由和波长。RWA问题属于组合优化问题的一类。发现RWA问题的最优解是np困难的,因此适合启发式方法。我们构造了一个整数线性规划(ILP)问题,将RWA问题建模为一个优化问题,并利用遗传算法(GA)启发式求解所构造的ILP,在多项式时间内得到一个近似最优解。我们的主要优化目标是建立个体之间拥塞最小的连接请求。次要目标是最小化跳数、路由长度、用于满足所有光路请求的光纤链路数量。在ARPANET (Advanced Research Project Agency NETwork)网络上对基于遗传算法的启发式算法进行了仿真,并将多目标遗传算法与单目标遗传算法的结果进行了比较。结果表明,在优化不同网络参数时,多目标遗传算法优于单目标遗传算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic Algorithm techniques to solve Routing and Wavelength Assignment problem in Wavelength Division Multiplexing all-optical networks
Routing and Wavelength Assignment (RWA) problem in Wavelength Division Multiplexed (WDM) optical networks assumes assigning the routes and wavelengths to be used to create the lightpaths on behalf of the connection requests. The RWA problem belongs to the class of combinatorial optimization problems. The optimal solution to the RWA problem is found to be NP-hard and thus suited to heuristic approaches. We formulate an Integer Linear Programming (ILP) problem to model the RWA problem as an optimization problem and solve the formulated ILP using Genetic Algorithm (GA) heuristic to obtain a near optimal solution in polynomial time. Our primary optimization objective is the establishment of connection requests with minimum congestion among the individuals. The secondary targets are to minimize the hop count, route length, the number of fiber links utilized to honor all the lightpath requests. The GA based heuristic approach is simulated on ARPANET (Advanced Research Project Agency NETwork) and the results obtained for the multi objective GA are compared with the single objective GA. The results show that multi objective GA performs better than single objective GA while optimizing different network parameters.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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:604180095
Book学术官方微信