Experimenting with Scalability of Floodlight Controller in Software
Experimenting with Scalability of Floodlight Controller in Software Defined Networks By: Saleh Asadollahi & Dr. Bhargavi Goswami asadollahimcitp@gmail. com bhargavihgowsami@gmail. com
Outline Experimenting with Scalability of Floodlight Controller in Software Defined Networks » Limitations of Current Networks » What is SDN? » Floodlight SDN Controller » SIMULATION ENVIRONMENT » Conclusion 2
Experimenting with Scalability of Floodlight Controller in Software Defined Networks Limitations of Current Networks » Lack of programmability and innovation » Enterprise networks are difficult to manage » “New control requirements have arisen”: » How to easily configure huge networks? 3 http: //www. excitingip. net/27/a-basic-enterprise-lan-network-architecture-block-diagram-and-components/
Experimenting with Scalability of Floodlight Controller in Software Defined Networks What is SDN Traditional vs SDN 4 Open. Flow/SDN tutorial, Srini Seetharaman, Deutsche Telekom, Silicon Valley Innovation Center
Experimenting with Scalability of Floodlight Controller in Software Defined Networks Floodlight SDN Controller Floodlight » open source » java based » web GUI Floodlight SDN Controller Architecture 5
Experimenting with Scalability of Floodlight Controller in Software Defined Networks SIMULATION ENVIRONMENT Connectivity between nodes in the scenario GUI of Floodlight Controller Environment 6
Result: throughput Experimenting with Scalability of Floodlight Controller in Software Defined Networks Throughput for 50 host Throughput for 150 host 7 Throughput for 300 host
Result: Latency Experimenting with Scalability of Floodlight Controller in Software Defined Networks Throughput for 50 host Throughput for 150 host 8 Throughput for 300 host
Experimenting with Scalability of Floodlight Controller in Software Defined Networks Conclusion With this paper, authors have made attempt to address the scalability features of the Floodlight controller by implementing various diversified scenarios in simulation experimental environment. In this paper, authors have provided the clear idea how to create experimental test bed with analysis of obtained statistical results keeping the performance as the central focus. We would conclude this paper by providing positive sign to move forward to the researchers who are looking for implementation of their idea over Floodlight Controller in the domain of Software Defined Networks without any doubt. The controller not just provide the simulation experimental test bed support but, also provides clear explanation for analysis of obtained statistics after the experiments are simulated. The tools suggested, simulated, shown through figures and graphs will help the research community to further conduct such experiments in the future by implementing their desired parameters though these experiments. This paper will also address the programmers, developers and new bees in the area of SDN, who are looking forward to touch the practical aspects of the SDN by following step by step implementations provided in the paper. Further, the research team will come up with few more papers on implementation of other SDN controllers in the coming future. The team also has planned to compare the controllers of SDN, once all the stellar controllers are implemented and experimented by them. 9
Experimenting with Scalability of Floodlight Controller in Software Defined Networks Conclusion 1. Asadollahi, S. , Gowsami, B. (2017). Revolution in Existing Network under the Influence of Software Defined Network. Proceedings of the INDIACom 11 th, Delhi, March 1 -3. 2017 IEEE Conference ID: 40353 2. Mc. Cauley, M. (2012). POX, from http: //www. noxrepo. org/ 3. Open. Daylight, Linux Foundation Collaborative Project, 2013, form http: //www. opendaylight. org 4. Erickson, D. (2013). The Beacon Open. Flow controller. Proceedings of ACM SIGCOMM Workshop Hot Topocs Software Defined Network II, 13 -18 p, 2013. 5. Nippon Telegraph and Telephone Corporation, RYU network operating system, 2012, from http: //osrg. github. com/ryu 6. Gude al, N. (2008). NOX: Towards an operating system for networks. ACM SIGCOMM - Computer Communication Revie. vol. 38, no. 3, pp. 105– 110 7. Asadollahi, S. , Gowsami, B. (2017). Software Defined Network, Controller Comparison. Proceedings of Tec'afe 2017, Vol. 5, Special Issue 2, April 2017. ISSN: 2320 -9798. 8. Mc. Keown et al, N. (2008). Open. Flow: Enabling innovation in campus networks. ACM SIGCOMM Computer Communication Revie, vol. 38, no. 2, p. 69– 74. 9. Smith et al, M. (2014). Op. Flex control protocol, Internet Engineering Task Force, from : http: // tools. ietf. org/html/draft-smith-opflex-00 10. Enns, R. , Bjorklund, M. , Schoenwaelder, J. , Bierman, A. (2011). Network configuration protocol (NETCONF). Internet Engineering Task Forc, form http: //www. ietf. org/rfc 6241. txt 11. Doria et al, A. (2010). Forwarding and control element separation (For. CES) protocol specification. Internet Engineering Task Forc, from http: //www. ietf. org/r/fc/rfc 5810. txt. 12. Song, H. (2013). Protocol-oblivious forwarding: Unleash the power of SDN through a future-proof forwarding plane. Proceedings of ACM SIGCOMM Workshop Hot Topics Softw Defined Netw II. p. 127– 132. 13. Sundaresan, S. , de donato, W. , Feamster, N. , Teixeira, R. , Crawford, S. (2011). A. Broadband internet performance: a view from the gateway. Proceedings of the ACM SIGCOMM , Aug. 2011. 14. Casado, M. , Freedman, M. J. , Pettit, J. , Luo, J. , Mckeown, N. , Shenker, S. Ethane. (2007). taking control of the enterprise. SIGCOMM CCR. p 1– 12. 15. Project Floodlight, Floodlight. (2012). from http: //floodlight. openflowhub. org/ 16. Lantz, B. Heller, and N. Mc. Keown. (2010). A network in a laptop: Rapid prototyping for software-defined network. Proceedings of ACM SIGCOMM Workshop Hot Topics Netw, 19 th. p. 19: 1– 19: 6 17. B. Pfaff and B. Davie. (2013). The Open v. Switch database management protocol. Internet Engineering Task Force, RFC 7047, from http: //www. ietf. org/rfc 7047. txt 10
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