利用商品SDN系统对大象流进行实时检测、隔离和监控

S. Madanapalli, Minzhao Lyu, Himal Kumar, H. Gharakheili, V. Sivaraman
{"title":"利用商品SDN系统对大象流进行实时检测、隔离和监控","authors":"S. Madanapalli, Minzhao Lyu, Himal Kumar, H. Gharakheili, V. Sivaraman","doi":"10.1109/NOMS.2018.8406200","DOIUrl":null,"url":null,"abstract":"Operators of enterprise and carrier networks in-creasingly require real-time visibility into traffic patterns in their network, so they can do better resource management (congestion detection, dynamic routing, capacity scheduling) and security protection (detection of intrusions and volumetric attacks). Of particular interest are elephant flows that transfer large volumes, since they demand most resources and can inflict most damage. Today's techniques for detecting and monitoring elephant flows are based on software-based packet analysis or hardware-based inspection, which are either unscalable or expensive. In this paper we design, implement, and evaluate an SDN-based solution that is scalable (to tens of Gigabits-per-second) and inexpensive (built using commodity OpenFlow switches). We first develop a system architecture that judiciously combines software packet inspection with hardware flow-table counters to identify and monitor heavy flows. We then use real traffic traces taken from a campus network to tune our algorithm parameters for desired trade-off between software load and hardware table size. Finally, we prototype our solution on a commodity OpenFlow hardware switch together with open-source controller and packet inspection software, and demonstrate operation at 10Gbps in a real campus network.","PeriodicalId":19331,"journal":{"name":"NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium","volume":"88 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Real-time detection, isolation and monitoring of elephant flows using commodity SDN system\",\"authors\":\"S. Madanapalli, Minzhao Lyu, Himal Kumar, H. Gharakheili, V. Sivaraman\",\"doi\":\"10.1109/NOMS.2018.8406200\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Operators of enterprise and carrier networks in-creasingly require real-time visibility into traffic patterns in their network, so they can do better resource management (congestion detection, dynamic routing, capacity scheduling) and security protection (detection of intrusions and volumetric attacks). Of particular interest are elephant flows that transfer large volumes, since they demand most resources and can inflict most damage. Today's techniques for detecting and monitoring elephant flows are based on software-based packet analysis or hardware-based inspection, which are either unscalable or expensive. In this paper we design, implement, and evaluate an SDN-based solution that is scalable (to tens of Gigabits-per-second) and inexpensive (built using commodity OpenFlow switches). We first develop a system architecture that judiciously combines software packet inspection with hardware flow-table counters to identify and monitor heavy flows. We then use real traffic traces taken from a campus network to tune our algorithm parameters for desired trade-off between software load and hardware table size. Finally, we prototype our solution on a commodity OpenFlow hardware switch together with open-source controller and packet inspection software, and demonstrate operation at 10Gbps in a real campus network.\",\"PeriodicalId\":19331,\"journal\":{\"name\":\"NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium\",\"volume\":\"88 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NOMS.2018.8406200\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NOMS.2018.8406200","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

摘要

企业和运营商网络的运营商越来越需要实时了解其网络中的流量模式,以便他们可以更好地进行资源管理(拥塞检测、动态路由、容量调度)和安全保护(检测入侵和容量攻击)。特别令人感兴趣的是运输大量货物的大象流,因为它们需要的资源最多,造成的破坏也最大。目前用于检测和监视象流的技术是基于基于软件的数据包分析或基于硬件的检查,这些技术要么不可扩展,要么代价高昂。在本文中,我们设计、实现并评估了一个基于sdn的解决方案,该解决方案可扩展(到每秒数十千兆)且价格低廉(使用商用OpenFlow交换机构建)。我们首先开发了一个系统架构,该架构明智地将软件数据包检测与硬件流表计数器相结合,以识别和监控大流量。然后,我们使用从校园网获取的真实流量跟踪来调整算法参数,以便在软件负载和硬件表大小之间进行所需的权衡。最后,我们在商用OpenFlow硬件交换机上对我们的解决方案进行了原型设计,以及开源控制器和数据包检测软件,并在真实的校园网中演示了10Gbps的运行。
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
Real-time detection, isolation and monitoring of elephant flows using commodity SDN system
Operators of enterprise and carrier networks in-creasingly require real-time visibility into traffic patterns in their network, so they can do better resource management (congestion detection, dynamic routing, capacity scheduling) and security protection (detection of intrusions and volumetric attacks). Of particular interest are elephant flows that transfer large volumes, since they demand most resources and can inflict most damage. Today's techniques for detecting and monitoring elephant flows are based on software-based packet analysis or hardware-based inspection, which are either unscalable or expensive. In this paper we design, implement, and evaluate an SDN-based solution that is scalable (to tens of Gigabits-per-second) and inexpensive (built using commodity OpenFlow switches). We first develop a system architecture that judiciously combines software packet inspection with hardware flow-table counters to identify and monitor heavy flows. We then use real traffic traces taken from a campus network to tune our algorithm parameters for desired trade-off between software load and hardware table size. Finally, we prototype our solution on a commodity OpenFlow hardware switch together with open-source controller and packet inspection software, and demonstrate operation at 10Gbps in a real campus network.
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
SSH Kernel: A Jupyter Extension Specifically for Remote Infrastructure Administration Visual emulation for Ethereum's virtual machine Analyzing throughput and stability in cellular networks Network events in a large commercial network: What can we learn? Economic incentives on DNSSEC deployment: Time to move from quantity to quality
×
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