A Heavy Hitter Detection Mechanism in Software Defined Networks

doi:10.13190/j.jbupt.2019-076

Journal of Beijing University of Posts and Telecommunications ›› 2020, Vol. 43 ›› Issue (1): 97-103.doi: 10.13190/j.jbupt.2019-076

• Reports • Previous Articles Next Articles

A Heavy Hitter Detection Mechanism in Software Defined Networks

XING Chang-you¹, LI Dong-yang¹, XIE Sheng-xu¹, ZHANG Guo-min¹, WEI Wei²

1. Army Engineering University, Command and Control Engineering College, Nanjing 210001, China;
2. Corps 31106, Nanjing 210016, China

Received:2019-05-11 Online:2020-02-28 Published:2020-03-27
Supported by:

Abstract

Abstract: SampleFlow, a heavy hitter detection mechanism in software defined networks, is proposed to solve the problems of low detection accuracy and high measurement cost. By combining the technical advantage of sFlow and OpenFlow, SampleFlow firstly detects a set of suspicious heavy hitters by using the coarse-grained sFlow sampling method, and then installs measurement flow entries on specific OpenFlow switches to perform a fine-grained measurement on these suspicious heavy hitters, so as to determine the true heavy hitters. Besides, SampleFlow also uses a sampling position optimization method to decrease the sampling redundancy. Experiment results show that SampleFlow can decrease the measurement cost, and increase the heavy hitter detection accuracy effectively.

Key words: software defined network, network measurement, heavy hitter detection, sampling

CLC Number:

TP393

XING Chang-you, LI Dong-yang, XIE Sheng-xu, ZHANG Guo-min, WEI Wei. A Heavy Hitter Detection Mechanism in Software Defined Networks[J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(1): 97-103.

References

[1] The Internet Society. Cisco systems NetFlow services export version 9[EB/OL]. (2004-10)[2019-04-15]. http://www.rfc-editor.org/rfc/rfc3954.
[2] InMon. Traffic monitoring using sFlow[EB/OL]. (2013-03)[2019-04-15]. https://sflow.org/sFlow-Overview.pdf.
[3] Mai J, Chuah C N, Sridharan A, et al. Is sampled data sufficient for anomaly detection[C]//2006 ACM SIGCOMM Conference on Internet Measurement. Rio De Janeiro:ACM, 2006:165-176.
[4] Kekely L, Kucera J, Pus V, et al. Software defined monitoring of application protocols[J]. IEEE Transactions on Computers, 2016, 65(2):615-626.
[5] Yuan L, Chuah C N, Mohapatra P. ProgME:towards programmable network measurement[J]. IEEE/ACM Transactions on Networking, 2011, 19(1):115-128.
[6] Yang Tong, Jiang Jie, Liu Peng, et al. Elastic sketch:adaptive and fast network-wide measurements[C]//2018 ACM SIGCOMM Conference. Budapest:ACM, 2018:561, 575.
[7] Moshref M, Yu M, Govindan R. Resource/accuracy tradeoffs in software-defined measurement[C]//2013 ACM SIGCOMM HotSDN. Hong Kong:ACM, 2013:73-78.
[8] Harrison R, Cai Q, Gupta A, et al. Network-wide heavy hitter detection with commodity switches[C]//2018 ACM Symposium on SDN Research. Los Angeles:ACM, 2018:1-7.
[9] Moshref M, Yu M, Govindan R, et al. DREAM:dynamic resource allocation for software-defined measurement[J]. ACM SIGCOMM Computer Communication Review, 2014, 44(4):419-430.
[10] Xing Changyou, Ding Ke, Hu Chao, et al. Sample and fetch-based large flow detection mechanism in software defined networks[J]. IEEE Communications Letters, 2016, 20(9):1764-1767.
[11] Suh J, Kwon T T, Dixon C, et al. OpenSample:a low-latency, sampling-based measurement platform for commodity SDN[C]//2014 IEEE International Conference on Distributed Computing Systems. Madrid:IEEE Press, 2014:228-237.
[12] MattR. 2004 Abilene dataset[EB/OL]. (2004-05-15)[2019-04-16]. http://www.maths.adelaide.edu.au/matthew.roughan/project/traffic_matrix/.
[13] Medina A, Lakhina A, Matta I, et al. BRITE:an approach to universal topology generation[C]//2001 International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems. Cincinnati:IEEE, 2001:346-353.
[14] CAIDA. Anonymized internet traces 2014[EB/OL]. (2014-10-09)[2019-04-17]. http://www.caida.org/data/passive/passive_2014_dataset.xml.

[1]	. Cooperative Offloading and Resource Allocation Algorithm of Multi-edge Nodes in VEC [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(2): 78-83.
[2]	LI Jingbo, MA Li, MA Dongchao, FU Yingxun, LI Yang. SDN-Based Integrated Convergent Network Routing Scheduling Mechanism [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(4): 84-90.
[3]	. SDN-based integrated convergent network routing scheduling mechanism [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(4): 98-104.
[4]	JIA Yuning, WEI Yifei, ZHOU Junhua. Service Function Chain Orchestrating Algorithm Based on SDN and NFV [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(2): 85-90.
[5]	LIU Shao-hua, LI Ming-hao, LI Zhao-xin, MAO Tian-lu, LIU Jing. Neural Radiance Field by Joint Sampling [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(6): 109-115.
[6]	SHAO Yu-bin, LIU Jing, LONG Hua, DU Qing-zhi, LI Yi-min. Language Identification Based on Vocal Tract Spectrum Parameters [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(3): 112-119.
[7]	MA Lu, LIU Ming, LI Chao, LU Zhao-ming, MA Huan. A Cloud-Edge Collaborative Computing Task Scheduling Algorithm for 6G Edge Networks [J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(6): 66-73.
[8]	LIU Han. Spam Web Detection Based on Hybrid-Sampling and Genetic Algorithm [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(6): 111-117.
[9]	YI Zhi-ling, CUI Chun-feng, HAN Shuang-feng, PAN Cheng-kang, CHEN Ya-mi. Analysis of Key Technologies of 5G-Oriented Cellular Internet of Things [J]. Journal of Beijing University of Posts and Telecommunications, 2018, 41(5): 20-25.
[10]	YIN Bi-bai, LIU Jiang, ZHANG Ran, HUANG Tao, LIU Yun-jie. NDN Routing Strategy Based on SDN Centralized Topology Update [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2018, 41(4): 1-8.
[11]	WU Hao, LI Yang, ZHANG Chu-wen, LIU Bin. The Hardware Measurement System for High-Speed Network Flow [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2017, 40(s1): 24-28.
[12]	QU Hua, ZHAO Ji-hong, FAN Bin, WANG Mi, GUO Ya. Ant Colony Optimization for Load Balance in Software Defined Network [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2017, 40(3): 51-55.
[13]	YU Yang, LIANG Man-gui, WANG Zhe. Software Defined Data Center Networks [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2017, 40(1): 57-61.
[14]	FEI Ning, CHEN Chun-ling, MAO Yan-qin. Design, Implementation and Evaluation of ASIC-Based OpenFlow Switch [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2016, 39(6): 93-98.
[15]	LI Yang, WU Hao, LIU Bin. The Hardware Implementation of Adaptive Non-Linear Sampling Algorithm [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2016, 39(3): 85-90.

A Heavy Hitter Detection Mechanism in Software Defined Networks

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments