Generic Method for SDN Controller Selection Using AHP and TOPSIS Methods

D. Kannan, Revathi Thiyagarajan, G. Shenbagalakshmi
{"title":"Generic Method for SDN Controller Selection Using AHP and TOPSIS Methods","authors":"D. Kannan, Revathi Thiyagarajan, G. Shenbagalakshmi","doi":"10.1142/s0219622022500067","DOIUrl":null,"url":null,"abstract":"The control plane plays an essential role in the implementation of Software Defined Network (SDN) architecture. Basically, the control plane is an isolated process and operates on control layer. The control layer encompasses controllers which provide a global view of the entire SDN. The Controller selection is more crucial for the network administrator to meet the specific use case. This research work mainly focuses on obtaining a better SDN controller. Initially, the SDN controllers are selected using integrated Analytic Hierarchy Process and Technique for Order Preference Similarity to Ideal Solution (AHP and TOPSIS) method. It facilitates to select minimal number of controllers based on their features in the SDN application. Finally, the performance evaluation is carried out using the CBENCH tool considering the best four ranked controllers obtained from the previous step. In addition, it is validated with the real-time internet topology such as Abilene and ERNET considering the delay factor. The result shows that the “Floodlight” controller responds better for latency and throughput. The selection of an optimum controller-Floodlight, using the real-world Internet topologies, outperforms in obtaining the path with a 28.57% decrease in delay in Abilene and 16.94% in ERNET. The proposed work can be applied in high traffic SDN applications.","PeriodicalId":13527,"journal":{"name":"Int. J. Inf. Technol. Decis. Mak.","volume":"130 1","pages":"1031-1059"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Inf. Technol. Decis. Mak.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s0219622022500067","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

The control plane plays an essential role in the implementation of Software Defined Network (SDN) architecture. Basically, the control plane is an isolated process and operates on control layer. The control layer encompasses controllers which provide a global view of the entire SDN. The Controller selection is more crucial for the network administrator to meet the specific use case. This research work mainly focuses on obtaining a better SDN controller. Initially, the SDN controllers are selected using integrated Analytic Hierarchy Process and Technique for Order Preference Similarity to Ideal Solution (AHP and TOPSIS) method. It facilitates to select minimal number of controllers based on their features in the SDN application. Finally, the performance evaluation is carried out using the CBENCH tool considering the best four ranked controllers obtained from the previous step. In addition, it is validated with the real-time internet topology such as Abilene and ERNET considering the delay factor. The result shows that the “Floodlight” controller responds better for latency and throughput. The selection of an optimum controller-Floodlight, using the real-world Internet topologies, outperforms in obtaining the path with a 28.57% decrease in delay in Abilene and 16.94% in ERNET. The proposed work can be applied in high traffic SDN applications.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于AHP和TOPSIS方法的SDN控制器选择通用方法
控制平面在实现软件定义网络(SDN)体系结构中起着至关重要的作用。基本上,控制平面是一个孤立的过程,并在控制层上运行。控制层包括提供整个SDN全局视图的控制器。对于网络管理员来说,控制器的选择对于满足特定用例更为重要。本文的研究工作主要是为了获得一个更好的SDN控制器。首先,采用层次分析法(AHP)和TOPSIS (Order Preference Similarity to Ideal Solution)方法选择SDN控制器。它便于在SDN应用中根据控制器的特性选择最少数量的控制器。最后,利用CBENCH工具对前一步得到的最佳4个排序控制器进行性能评估。并在考虑延迟因素的实时网络拓扑如Abilene和ERNET上进行了验证。结果表明,“泛光灯”控制器对延迟和吞吐量的响应更好。选择最优控制器-泛光灯,使用现实世界的互联网拓扑,在获得路径方面表现出色,在Abilene中延迟减少28.57%,在ERNET中延迟减少16.94%。该工作可以应用于高流量的SDN应用。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Guest Editors' Introduction for the Special Issue on The Role of Decision Making to Overcome COVID-19 The Behavioral TOPSIS Based on Prospect Theory and Regret Theory Instigating the Sailfish Optimization Algorithm Based on Opposition-Based Learning to Determine the Salient Features From a High-Dimensional Dataset Optimized Deep Learning-Enabled Hybrid Logistic Piece-Wise Chaotic Map for Secured Medical Data Storage System A Typology Scheme for the Criteria Weighting Methods in MADM
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1