基于混合跳跃基因遗传算法的多目标路由请求调度方法

M. Rahman, S. Mondol, G. S. Hossain, A. Dey
{"title":"基于混合跳跃基因遗传算法的多目标路由请求调度方法","authors":"M. Rahman, S. Mondol, G. S. Hossain, A. Dey","doi":"10.1109/ICICT.2007.375405","DOIUrl":null,"url":null,"abstract":"This paper presents a hybrid jumping genes genetic algorithm (HJGGA) for solving the request scheduling problem in multiple destination routing (MDR). The problem incorporates the scheduling and routing process of a set of requests having single source and multiple destinations through a network. Our proposed HJGGA framework, that facilitates intelligent splitting of bandwidth requirement of requests as well as multiple optimal paths for transmission, searches for a near-optimal scheduling solution. We have also developed new chromosome-encoding and mutation technique for our HJGGA. Experimental result shows that our scheme reflects better real world situations and performs superior than previous researches.","PeriodicalId":206443,"journal":{"name":"2007 International Conference on Information and Communication Technology","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Hybrid Jumping Genes Genetic Algorithm Based Request Scheduling Approach in Multiple Destination Routing\",\"authors\":\"M. Rahman, S. Mondol, G. S. Hossain, A. Dey\",\"doi\":\"10.1109/ICICT.2007.375405\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a hybrid jumping genes genetic algorithm (HJGGA) for solving the request scheduling problem in multiple destination routing (MDR). The problem incorporates the scheduling and routing process of a set of requests having single source and multiple destinations through a network. Our proposed HJGGA framework, that facilitates intelligent splitting of bandwidth requirement of requests as well as multiple optimal paths for transmission, searches for a near-optimal scheduling solution. We have also developed new chromosome-encoding and mutation technique for our HJGGA. Experimental result shows that our scheme reflects better real world situations and performs superior than previous researches.\",\"PeriodicalId\":206443,\"journal\":{\"name\":\"2007 International Conference on Information and Communication Technology\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Information and Communication Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICT.2007.375405\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Information and Communication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICT.2007.375405","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

针对多目的路由(MDR)中的请求调度问题,提出了一种混合跳跃基因遗传算法(HJGGA)。该问题包含了一组通过网络具有单个源和多个目的地的请求的调度和路由过程。我们提出的HJGGA框架,有利于智能分割请求的带宽需求和多条最优传输路径,搜索一个接近最优的调度解决方案。我们还开发了新的HJGGA染色体编码和突变技术。实验结果表明,该方案较好地反映了实际情况,性能优于以往的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Hybrid Jumping Genes Genetic Algorithm Based Request Scheduling Approach in Multiple Destination Routing
This paper presents a hybrid jumping genes genetic algorithm (HJGGA) for solving the request scheduling problem in multiple destination routing (MDR). The problem incorporates the scheduling and routing process of a set of requests having single source and multiple destinations through a network. Our proposed HJGGA framework, that facilitates intelligent splitting of bandwidth requirement of requests as well as multiple optimal paths for transmission, searches for a near-optimal scheduling solution. We have also developed new chromosome-encoding and mutation technique for our HJGGA. Experimental result shows that our scheme reflects better real world situations and performs superior than previous researches.
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