Full Text:   <3075>

Summary:  <1988>

CLC number: TP393

On-line Access: 2016-07-05

Received: 2015-10-21

Revision Accepted: 2016-03-30

Crosschecked: 2016-06-08

Cited: 2

Clicked: 7002

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Zhi-yang Li

http://orcid.org/0000-0002-5396-3447

-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2016 Vol.17 No.7 P.620-633

http://doi.org/10.1631/FITEE.1500350


A K self-adaptive SDN controller placement for wide area networks


Author(s):  Peng Xiao, Zhi-yang Li, Song Guo, Heng Qi, Wen-yu Qu, Hai-sheng Yu

Affiliation(s):  School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China; more

Corresponding email(s):   lizy0205@gmail.com

Key Words:  Software-defined networking (SDN), Controller placement, K self-adaptive method


Peng Xiao, Zhi-yang Li, Song Guo, Heng Qi, Wen-yu Qu, Hai-sheng Yu. A K self-adaptive SDN controller placement for wide area networks[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(7): 620-633.

@article{title="A K self-adaptive SDN controller placement for wide area networks",
author="Peng Xiao, Zhi-yang Li, Song Guo, Heng Qi, Wen-yu Qu, Hai-sheng Yu",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="17",
number="7",
pages="620-633",
year="2016",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1500350"
}

%0 Journal Article
%T A K self-adaptive SDN controller placement for wide area networks
%A Peng Xiao
%A Zhi-yang Li
%A Song Guo
%A Heng Qi
%A Wen-yu Qu
%A Hai-sheng Yu
%J Frontiers of Information Technology & Electronic Engineering
%V 17
%N 7
%P 620-633
%@ 2095-9184
%D 2016
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1500350

TY - JOUR
T1 - A K self-adaptive SDN controller placement for wide area networks
A1 - Peng Xiao
A1 - Zhi-yang Li
A1 - Song Guo
A1 - Heng Qi
A1 - Wen-yu Qu
A1 - Hai-sheng Yu
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 17
IS - 7
SP - 620
EP - 633
%@ 2095-9184
Y1 - 2016
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1500350


Abstract: 
As a novel architecture, software-defined networking (SDN) is viewed as the key technology of future networking. The core idea of SDN is to decouple the control plane and the data plane, enabling centralized, flexible, and programmable network control. Although local area networks like data center networks have benefited from SDN, it is still a problem to deploy SDN in wide area networks (WANs) or large-scale networks. Existing works show that multiple controllers are required in WANs with each covering one small SDN domain. However, the problems of SDN domain partition and controller placement should be further addressed. Therefore, we propose the spectral clustering based partition and placement algorithms, by which we can partition a large network into several small SDN domains efficiently and effectively. In our algorithms, the matrix perturbation theory and eigengap are used to discover the stability of SDN domains and decide the optimal number of SDN domains automatically. To evaluate our algorithms, we develop a new experimental framework with the Internet2 topology and other available WAN topologies. The results show the effectiveness of our algorithm for the SDN domain partition and controller placement problems.

The paper proposes Spectral Clustering based partition and placement algorithms to solve the controller placement problem for multi-domain SDN. The paper is with good theories and experiment evaluations.

一种K自适应的广域网SDN控制器部署方法

目的:软件定义网络(software-defined networking)作为一种新技术框架,正成为未来网络技术的核心。软件定义网络的核心思想就是控制平面和数据平面分离,方便管理和控制编程。虽然软件定义网络已在数据中心这样的局域网中得到了应用和部署,但在更大规模的广域网上部署依然面临着很多问题,如SDN域划分、控制器部署等问题。本文提出了一种基于谱的SDN控制器部署方法,通过此方法能将较大的网络划分成小的SDN域并选择其控制器位置。通过分析模型的矩阵扰动和本征间隙,能够自动得到SDN域个数,以达到较好的划分效果和控制器部署方案。
创新点:提出基于谱的SDN控制器部署模型,以解决广域网SDN域划分及控制器部署问题;通过分析模型,提出一种K自适应的广域网SDN控制器部署方法,能够自动得到SDN域个数,以达到较好的划分效果和控制器部署方案。
方法:通过分析模型的矩阵扰动和本征间隙,能够自动得到SDN域个数,以达到较好的划分效果和控制器部署方案。结合广域网拓扑和SDN平台建立了仿真实验框架,利用该框架进行相关实验,验证模型的准确性和有效性。
结论:本文的方法能较好的解决SDN域划分和控制器部署问题(图3、5)。K自适应方法所得到的结果与实际划分效果一致(图6-11)。

关键词:软件定义网络;控制器部署;K自适应方法

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Bach, F.R., Jordan, M.I., 2003. Learning Spectral Clustering. Technical Report, No. UCB/CSD-03-1249. University of California at Berkeley, USA.

[2]Cai, Z., Cox, A.L., Ng, T.S.E., 2010. Maestro: a system for scalable OpenFlow control. Technical Report, TR10-08. Rice University, USA.

[3]Dixit, A., Hao, F., Mukherjee, S., et al., 2013. Towards an elastic distributed SDN controller. ACM SIGCOMM Comput. Commun. Rev., 43(4):7-12.

[4]Erickson, D., 2013. The beacon OpenFlow controller. Proc. 2nd ACM SIGCOMM Workshop on Hot Topics in Software Defined Networking, p.13-18.

[5]Gude, N., Koponen, T., Pettit, J., et al., 2008. NOX: towards an operating system for networks. ACM SIGCOMM Comput. Commun. Rev., 38(3):105-110.

[6]Heller, B., Sherwood, R., McKeown, N., 2012. The controller placement problem. Proc. 1st Workshop on Hot Topics in Software Defined Networks, p.7-12.

[7]Hock, D., Hartmann, M., Gebert, S., et al., 2013. Pareto-optimal resilient controller placement in SDN-based core networks. Proc. 25th Int. Teletraffic Congress, p.1-9.

[8]Kirkpatrick, K., 2013. Software-defined networking. Commun. ACM, 56(9):16-19.

[9]Knight, S., Nguyen, H.X., Falkner, N., et al., 2011. The Internet topology zoo. IEEE J. Sel. Areas Commun., 29(9):1765-1775.

[10]Koponen, T., Casado, M., Gude, N., et al., 2010. Onix: a distributed control platform for large-scale production networks. Proc. OSDI, p.1-14.

[11]Kreutz, D., Ramos, F.M.V., Veríssimo, P.E., et al., 2015. Software-defined networking: a comprehensive survey. Proc. IEEE, 103(1):14-76.

[12]Lin, P., Bi, J., Wang, Y., 2013. East-west bridge for SDN network peering. Proc. 2nd CCF Int. Conf. of China, p.170-181.

[13]Liu, N., Lu, Y., Tang, X.J., et al., 2014. Study on automatically determining the optimal number of clusters present in spectral co-clustering documents and words. J. Chin. Comput. Syst., 35(3):610-614 (in Chinese).

[14]Mall, R., Langone, R., Suykens, J.A.K., 2013. Self-tuned kernel spectral clustering for large scale networks. Proc. IEEE Int. Conf. on Big Data, p.385-393.

[15]McKeown, N., Anderson, T., Balakrishnan, H., et al., 2008. OpenFlow: enabling innovation in campus networks. ACM SIGCOMM Comput. Commun. Rev., 38(2):69-74.

[16]Ng, A.Y., Jordan, M.I., Weiss, Y., 2001. On spectral clustering: analysis and an algorithm. In: Dietterich, T.G., Becker, S., Ghahramani, Z. (Eds.). Advances in Neural Information Processing Systems 14, p.849-856.

[17]Phemius, K., Bouet, M., Leguay, J., 2014. DISCO: distributed multi-domain SDN controllers. Proc. IEEE Network Operations and Management Symp., p.1-4.

[18]Rebagliati, N., Verri, A., 2011. Spectral clustering with more than $K$ eigenvectors. Neurocomputing, 74(9):1391-1401.

[19]Shah, S.A., Faiz, J., Farooq, M., et al., 2013. An architectural evaluation of SDN controllers. Proc. IEEE Int. Conf. on Communications, p.3504-3508.

[20]Shalimov, A., Zuikov, D., Zimarina, D., et al., 2013. Advanced study of SDN/OpenFlow controllers. Proc. 9th Central & Eastern European Software Engineering Conf. in Russia, Article 1.

[21]Shi, J., Malik, J., 2000. Normalized cuts and image segmentation. IEEE Trans. Patt. Anal. Mach. Intell., 22(8):888-905.

[22]Tam, A.S.W., Xi, K., Chao, H.J., 2011. Use of devolved controllers in data center networks. Proc. IEEE Conf. on Computer Communications Workshops, p.596-601.

[23]Tian, Z., Li, X., Ju, Y., 2007. Spectral clustering based on matrix perturbation theory. Sci. China Ser. F, 50(1):63-81.

[24]Tootoonchian, A., Ganjali, Y., 2010. HyperFlow: a distributed control plane for OpenFlow. Proc. Int. Network Management Conf. on Research on Enterprise Networking, p.1-6.

[25]Tootoonchian, A., Gorbunov, S., Ganjali, Y., et al., 2012. On controller performance in software-defined networks. Proc. 2nd USENIX Conf. on Hot Topics in Management of Internet, Cloud, and Enterprise Networks and Services, p.1-6.

[26]von Luxburg, U., 2007. A tutorial on spectral clustering. Stat. Comput., 17(4):395-416.

[27]Wang, L., Bo, L.F., Jiao, L.C., 2007. Density-sensitive spectral clustering. Acta Electron. Sin., 35(8):1577-1581 (in Chinese).

[28]Wauthier, F.L., Jojic, N., Jordan, M.I., 2012. Active spectral clustering via iterative uncertainty reduction. Proc. 18th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, p.1339-1347.

[29]Xiao, P., Qu, W., Li, Z., 2014. The SDN controller placement problem for WAN. Proc. IEEE/CIC Int. Conf. on Communications in China, p.220-224.

[30]Xie, H., Tsou, T., Lopez, D., et al., 2012. Software-Defined Networking Efforts Debuted at IETF 84. Available from http://www.internetsociety.org/articles/software-defined-networking-efforts-debuted-ietf-84.

[31]Yin, H., Xie, H., Tsou, T., et al., 2012. SDNi: a Message Exchange Protocol for Software Defined Networks (SDNS) across Multiple Domains. Available from https://tools.ietf.org/html/draft-yin-sdn-sdni-00.

[32]Yu, M., Rexford, J., Freedman, M.J., et al., 2010. Scalable flow-based networking with DIFANE. ACM SIGCOMM Comput. Commun. Rev., 40(4):351-362.

[33]Zelnik-Manor, L., Perona, P., 2004. Self-tuning spectral clustering. In: Saul, L.K., Weiss, Y., Bottou, L. (Eds.), Advances in Neural Information Processing Systems 17, p.1601-1608.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE