A Novel Software-Defined Networking Controller : the Distributed Active Information Model (DAIM)

• Autorzy: Pupatwibul P. , Banjar A. , Hossain M. I. , Braun R. , Moulton B.

Identyfikatory

DOI

10.24425/119372

• Języki publikacji: EN

Abstrakty

EN

This paper presents a new OpenFlow controller: the Distributed Active Information Model (DAIM). The DAIM controller was developed to explore the viability of a logically distributed control plane. It is implemented in a distributed way throughout a software-defined network, at the level of the switches. The method enables local process flows, by way of local packet switching, to be controlled by the distributed DAIM controller (as opposed to a centralised OpenFlow controller). The DAIM ecosystem is discussed with some sample code, together with flowcharts of the implemented algorithms. We present implementation details, a testing methodology, and an experimental evaluation. A performance analysis was conducted using the Cbench open benchmarking tool. Comparisons were drawn with respect to throughput and latency. It is concluded that the DAIM controller can handle a high throughput, while keeping the latency relatively low. We believe the results to date are potentially very interesting, especially in light of the fact that a key feature of the DAIM controller is that it is designed to enable the future development of autonomous local flow process and management strategies.

Słowa kluczowe

EN

distributed network; OpenFlow; DAIM model; software defined networking; next generation networks

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2018
• Tom: Vol. 64, No. 2
• Strony: 209--216
• Opis fizyczny: Bibliogr. 13 poz., rys., wykr.

Twórcy

autor

Pupatwibul P.

• Centre for Real-Time Information Networks (CRIN), University of Technology, Sydney, Australia

autor

Banjar A.

• Centre for Real-Time Information Networks (CRIN), University of Technology, Sydney, Australia

autor

Hossain M. I.

• Centre for Real-Time Information Networks (CRIN), University of Technology, Sydney, Australia

autor

Braun R.

• Centre for Real-Time Information Networks (CRIN), University of Technology, Sydney, Australia

autor

Moulton B.

• Centre for Real-Time Information Networks (CRIN), University of Technology, Sydney, Australia

Bibliografia

• [1] O. N. Foundation, “Software-defined networking: The new norm for networks,” ONF White Paper, vol. 2, pp. 2-6, 2012.
• [2] N. McKeown, T. Anderson, H. Balakrishnan, G. Parulkar, L. Peterson, J. Rexford, S. Shenker, and J. Turner, “Openflow: enabling innovation in campus networks,” ACM SIGCOMM Computer Communication Review, vol. 38, no. 2, pp. 69-74, 2008.
• [3] D. Jankowski and M. Amanowicz, “On efficiency of selected machine learning algorithms for intrusion detection in software defined networks,” International Journal of Electronics and Telecommunications, vol. 62, no. 3, pp. 247-252, 2016.
• [4] I. Guis, “Enterprise data center networks,” Open Networking Summit 2012, 2012.
• [5] L. R. Bays and D. S. Marcon, “Flow based load balancing: Optimizing web servers resource utilization,” Journal of Applied Computing Research, vol. 1, no. 2, pp. 76-83, 2011.
• [6] S. Hassas Yeganeh and Y. Ganjali, “Kandoo: a framework for efficient and scalable offloading of control applications,” in Proceedings of the first workshop on Hot topics in software defined networks. ACM, 2012, pp. 19-24.
• [7] A. Tootoonchian and Y. Ganjali, “Hyperflow: A distributed control plane for openflow,” in Proceedings of the 2010 internet network management conference on Research on enterprise networking, 2010, pp. 3-3.
• [8] T. Koponen, M. Casado, N. Gude, J. Stribling, L. Poutievski, M. Zhu, R. Ramanathan, Y. Iwata, H. Inoue, T. Hama et al., “Onix: A distributed control platform for large-scale production networks.” in OSDI, vol. 10, 2010, pp. 1-6.
• [9] A. Banjar, P. Pupatwibul, and R. Braun, “Daim: a mechanism to distribute control functions within openflow switches.” JNW, vol. 9, no. 1, pp. 1-9, 2014.
• [10] P. Pupatwibul, A. Banjar, and R. Braun, “Using daim as a reactive interpreter for openflow networks to enable autonomic functionality,” ACM SIGCOMM Computer Communication Review, vol. 43, no. 4, pp. 523-524, 2013.
• [11] P. Pupatwibul, A. Banjar, A. Al Sabbagh, and R. Braun, “A comparative review: Accurate openflow simulation tools for prototyping.” JNW, vol. 10, no. 5, pp. 322-327, 2015.
• [12] P. Pupatwibul, A. Banjar, A. A. Sabbagh, and R. Braun, “An intelligent model for distributed systems in next generation networks,” in Advanced Methods and Applications in Computational Intelligence. Springer, 2014, pp. 315-334.
• [13] P. Pupatwibul, A. Banjar, A. Al Sabbagh, and R. Braun, “Developing an application based on openflow to enhance mobile ip networks,” in IEEE Conference on Local Computer Networks. IEEE, 2013.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).