TPEFD:an SDN-based efficient elephant flow detection method

doi:10.11959/j.issn.2096-109x.2017.00167

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TPEFD:an SDN-based efficient elephant flow detection method

Papers | 更新时间：2024-06-03

- TPEFD:an SDN-based efficient elephant flow detection method
- Chinese Journal of Network and Information Security Vol. 3, Issue 5, Pages: 70-76(2017)
- 作者机构：
  
  1. Faculty of Information Technology,Beijing University of Technology,Beijing 100124,China
  2. Key Laboratory of Trusted Computing,Beijing 100124,China
  3. Information Security Rank Protection Key Technology National Engineering Laboratory,Beijing 100124,China
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-109x.2017.00167
  CLC：
- Online First：2017-05，
  
  Published：15 May 2017
- 稿件说明：
移动端阅览
[J]. Chinese Journal of Network and Information Security, 2017, 3(5): 70-76.
DOI：

[J]. Chinese Journal of Network and Information Security, 2017, 3(5): 70-76. DOI： 10.11959/j.issn.2096-109x.2017.00167.

摘要

Software-defined networking (SDN) is a new approach to configure and operate programmable switches of the networks (especially the data center networks) through a centralized software controller.Elephant flows normally exist in data center networks and take up a large amount of network bandwidth

so the elephant flow detection is very important to ease network congestion.A two-phase real-time detection (TPEFD) method was proposed to detect the elephant flows in the SDN-based network.First

the controller obtained aggregated statistics and shrank sample scope until it was small enough

packets were sampled in the scope in switches.In order to identify the elephant flows

the sFlow sampling results were compared with the dynamic threshold.If the sampling value exceeded the threshold value

the flow was recognized as an elephant flow.The efficiency of our method in an SDN experimental environment was evaluated.The experimental results indicated that the proposed method was feasible and the detection time was efficient.

Abstract

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references

AZODOLMOLKY S . Software defined networking with OpenFlow [M ] . Birmingham : Packt PublishingPress , 2013 .

GREENBERGA , . VL2:a scalable and flexible data center network [C ] // ACM SIGCOMM Computer Communication Review . 2009 : 51 - 62 .

KANDULA S , SENGUPTA S , GREENBERG A , et al . The nature of data center traffic:measurements ＆analysis [C ] // ACM SIGCOMM Conference on Internet Measurement . 2009 : 202 - 208 .

BENSON T , AKELLA A , MALTZ D A . Network traffic characteristics of data centers in the wild [C ] // ACM SIGCOMM Conference on Internet Measurement . 2010 : 267 - 280 .

MORI T , KAWAHARA R , NAITO S , et al . On the characteristics of internet traffic variability:spikes and elephants [C ] // The International Symposium on Applications and the Internets . 2004 : 99 - 106 .

BENSON T , ANAND A,AKELLAA , et al . Understanding data center traffic characteristics [C ] // ACM Workshop on Research on Enterprise Networking . 2009 : 65 - 72 .

LIN C Y , CHEN C , CHANG J W , et al . Elephant flow detection in datacenters using OpenFlow-based hierarchical statistics pulling [C ] // Global Communications Conference . 2014 : 2264 - 2269 .

CHENG G , GONG J , DING W . Network traffic sampling model on packet identification [M ] // Berlin : SpringerPress , 2005 : 758 - 765 .

SHALIMOV A , ZUIKOV D , ZIMARINA D , et al . Advanced study of SDN/OpenFlow controllers [C ] // Central ＆Eastern European Software Engineering Conference . 2013 : 1 - 6 .

PHAAL P , PANCHEN S , MCKEE N . InMon corporation's sFlow:a method for monitoring traffic in switched and routed networks [M ] // RFC Editor , 2001 .

HUANG L , ZHI X , GAO Q , et al . Design and implementation of multicast routing system over SDN and sFlow [C ] // IEEE International Conference on Communication Software and Networks . 2016 : 524 - 529 .

EREL M , TEOMAN E , OZCEVIK Y , et al . Scalability analysis and flow admission control in mininet-based SDN environment [C ] // Network Function Virtualization and Software Defined Network . 2015 : 18 - 19 .

ESTAN C , VARGHESE G . New directions in traffic measurement and accounting [C ] // ACM SIGCOMM Workshop on Internet Measurement . 2001 : 75 - 80 .

CURTIS A R , MOGUL J C , TOURRILHES J , et al . DevoFlow:scaling flow management for high-performance networks [C ] // ACM SIGCOMM 2011 Conference on Applications,Technologies,Architectures,and Protocols for Computer Communications . 2011 : 254 - 265 .

WANG H , GONG Z H . Hits and holds:two algorithms for identifying the elephant flows [J ] . Journal of Software , 2010 , 21 ( 6 ): 1391 - 1403 .

AL-FARES M , RADHAKRISHNAN S , RAGHAVAN B , et al . Hedera:dynamic flow scheduling for data center networks [C ] // Usenix Symposium on Networked Systems Design and Implementation . 2010 : 281 - 296 .

CURTIS A R , KIM W , YALAGANDULA P . Mahout:low-overhead datacenter traffic management using end-host-based elephant detection [C ] // Infocom IEEE . 2011 : 1629 - 1637 .

BENSON T , ANAND A , AKELLA A , et al . MicroTE:fine grained traffic engineering for data centers [C ] // CONEXT . 2011 :8.

ZHOU W , LI L , LUO M , et al . Rest API design patterns for SDN northbound API [C ] // The International Conference on Advanced Information Networking and Applications Workshops . 2014 : 358 - 365 .

MORI T , UCHIDA M , KAWAHARA R , et al . Identifying elephant flows through periodically sampled packets [C ] // ACM SIGCOMM Conference on Internet Measurement . 2004 : 115 - 120 .

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