MD-IDN:软件定义基础设施中的多域意图驱动网络

Saeed Arezoumand, Kristina Dzeparoska, H. Bannazadeh, A. Leon-Garcia
{"title":"MD-IDN:软件定义基础设施中的多域意图驱动网络","authors":"Saeed Arezoumand, Kristina Dzeparoska, H. Bannazadeh, A. Leon-Garcia","doi":"10.23919/CNSM.2017.8256016","DOIUrl":null,"url":null,"abstract":"Intent-Driven Networking is recently gaining interest, with all major SDN control platforms now providing an intent Northbound Interface (NBI) as a high-level abstraction for network management. With these frameworks network operators can conveniently define “what needs to be done”, rather than “how it should be done”. Current IDN frameworks pose two main limitations that affect deployment in production grade and multi-domain networks. They are mainly concerned with a single network domain, and thus enabling end-to-end network intents over a multi-domain and large-scale setup is still a challenge. Furthermore, these frameworks do not consider any differentiation between user intents and provider intents, and a limited set of intent classes are available for both. In this paper we present MD-IDN, which provides an intent framework for the users of multi-domain cloud infrastructures. We first propose a graph-based abstraction model for user-defined intents and a generic intent compilation process. Then, we propose compilation algorithms to achieve scalability in multi-domain networks: First, user-defined intents get processed over an abstracted multi-graph of network domains and their interconnections, and a set of local intents will be generated for each of the involved domains. Afterwards, the local intents will be compiled and installed in local regions in parallel. MD-IDN is deployed as a public service in the SAVI Testbed over more than ten data centers spanning across Canada. In multi-domain environments, our experiments show that MD-IDN outperforms current practices that compile intents over a flat network topology.","PeriodicalId":211611,"journal":{"name":"2017 13th International Conference on Network and Service Management (CNSM)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"MD-IDN: Multi-domain intent-driven networking in software-defined infrastructures\",\"authors\":\"Saeed Arezoumand, Kristina Dzeparoska, H. Bannazadeh, A. Leon-Garcia\",\"doi\":\"10.23919/CNSM.2017.8256016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Intent-Driven Networking is recently gaining interest, with all major SDN control platforms now providing an intent Northbound Interface (NBI) as a high-level abstraction for network management. With these frameworks network operators can conveniently define “what needs to be done”, rather than “how it should be done”. Current IDN frameworks pose two main limitations that affect deployment in production grade and multi-domain networks. They are mainly concerned with a single network domain, and thus enabling end-to-end network intents over a multi-domain and large-scale setup is still a challenge. Furthermore, these frameworks do not consider any differentiation between user intents and provider intents, and a limited set of intent classes are available for both. In this paper we present MD-IDN, which provides an intent framework for the users of multi-domain cloud infrastructures. We first propose a graph-based abstraction model for user-defined intents and a generic intent compilation process. Then, we propose compilation algorithms to achieve scalability in multi-domain networks: First, user-defined intents get processed over an abstracted multi-graph of network domains and their interconnections, and a set of local intents will be generated for each of the involved domains. Afterwards, the local intents will be compiled and installed in local regions in parallel. MD-IDN is deployed as a public service in the SAVI Testbed over more than ten data centers spanning across Canada. In multi-domain environments, our experiments show that MD-IDN outperforms current practices that compile intents over a flat network topology.\",\"PeriodicalId\":211611,\"journal\":{\"name\":\"2017 13th International Conference on Network and Service Management (CNSM)\",\"volume\":\"90 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 13th International Conference on Network and Service Management (CNSM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/CNSM.2017.8256016\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 13th International Conference on Network and Service Management (CNSM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/CNSM.2017.8256016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18

摘要

意图驱动的网络最近引起了人们的兴趣,所有主要的SDN控制平台现在都提供意图北向接口(NBI)作为网络管理的高级抽象。有了这些框架,网络运营商可以方便地定义“需要做什么”,而不是“应该怎么做”。目前的IDN框架存在两个主要限制,影响在生产级和多域网络中的部署。它们主要关注单个网络域,因此在多域和大规模设置上实现端到端网络意图仍然是一个挑战。此外,这些框架没有考虑用户意图和提供者意图之间的任何区别,并且对两者都可用的一组有限的意图类。本文提出了MD-IDN,它为多域云基础设施的用户提供了一个意图框架。我们首先提出了一个基于图的用户定义意图抽象模型和一个通用的意图编译过程。然后,我们提出了在多域网络中实现可扩展性的编译算法:首先,在网络域及其相互联系的抽象多图上处理自定义意图,并为每个涉及的域生成一组本地意图;之后,本地意图将被并行编译并安装在本地区域中。MD-IDN作为公共服务部署在SAVI测试平台上,横跨加拿大的十多个数据中心。在多域环境中,我们的实验表明,MD-IDN优于当前在平面网络拓扑上编译意图的实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
MD-IDN: Multi-domain intent-driven networking in software-defined infrastructures
Intent-Driven Networking is recently gaining interest, with all major SDN control platforms now providing an intent Northbound Interface (NBI) as a high-level abstraction for network management. With these frameworks network operators can conveniently define “what needs to be done”, rather than “how it should be done”. Current IDN frameworks pose two main limitations that affect deployment in production grade and multi-domain networks. They are mainly concerned with a single network domain, and thus enabling end-to-end network intents over a multi-domain and large-scale setup is still a challenge. Furthermore, these frameworks do not consider any differentiation between user intents and provider intents, and a limited set of intent classes are available for both. In this paper we present MD-IDN, which provides an intent framework for the users of multi-domain cloud infrastructures. We first propose a graph-based abstraction model for user-defined intents and a generic intent compilation process. Then, we propose compilation algorithms to achieve scalability in multi-domain networks: First, user-defined intents get processed over an abstracted multi-graph of network domains and their interconnections, and a set of local intents will be generated for each of the involved domains. Afterwards, the local intents will be compiled and installed in local regions in parallel. MD-IDN is deployed as a public service in the SAVI Testbed over more than ten data centers spanning across Canada. In multi-domain environments, our experiments show that MD-IDN outperforms current practices that compile intents over a flat network topology.
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
期刊最新文献
Measuring exposure in DDoS protection services Connectivity extraction in cloud infrastructures An evolutionary controllers' placement algorithm for reliable SDN networks A lightweight snapshot-based DDoS detector Enforcing free roaming among EU countries: An economic analysis
×
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