Load Balancing in Software Defined Networking using Round Robin Algorithm
Software-Defined Networking (SDN) facilitates flexible network management by decoupling the control plane from the data plane, enabling centralized programmability. This paper presents a practical implementation of a load balancing system based on the Round Robin algorithm, developed for experimenta...
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| Formatua: | Conference paper |
| Hizkuntza: | Vietnamese |
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2025
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| Sarrera elektronikoa: | https://scholar.dlu.edu.vn/handle/123456789/4981 |
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| Thư viện lưu trữ: | Thư viện Trường Đại học Đà Lạt |
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oai:scholar.dlu.edu.vn:123456789-4981 |
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dspace |
| institution |
Thư viện Trường Đại học Đà Lạt |
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Thư viện số |
| language |
Vietnamese |
| topic |
Software-Defined Networking, Load Balancing, Round Robin, Mininet, ONOS, Tkinter, Network Visualization, Real-Time Monitoring. |
| spellingShingle |
Software-Defined Networking, Load Balancing, Round Robin, Mininet, ONOS, Tkinter, Network Visualization, Real-Time Monitoring. Trần, Vĩnh Phúc Trương, Công Thành Đặng, Đăng Nguyên Vũ, Duy Hoàng Load Balancing in Software Defined Networking using Round Robin Algorithm |
| description |
Software-Defined Networking (SDN) facilitates flexible network management by decoupling the control plane from the data plane, enabling centralized programmability. This paper presents a practical implementation of a load balancing system based on the Round Robin algorithm, developed for experimental and educational purposes in an SDN testbed using Mininet and the ONOS controller. The proposed setup involves a set of clients and servers interconnected through OpenFlow switches, with a standalone load balancer—deployed externally from the controller—sequentially forwarding traffic to available servers. A custom monitoring dashboard, built with Python and Tkinter, provides real-time visualization of network parameters including bandwidth, throughput, server load, and packet loss. Results from test scenarios show that the system achieves stable traffic distribution and effective resource utilization under varying network conditions. The work demonstrates the viability of lightweight traffic management strategies in SDN environments and serves as a baseline for further enhancements toward adaptive or intelligent control techniques. |
| format |
Conference paper |
| author |
Trần, Vĩnh Phúc Trương, Công Thành Đặng, Đăng Nguyên Vũ, Duy Hoàng |
| author_facet |
Trần, Vĩnh Phúc Trương, Công Thành Đặng, Đăng Nguyên Vũ, Duy Hoàng |
| author_sort |
Trần, Vĩnh Phúc |
| title |
Load Balancing in Software Defined Networking using Round Robin Algorithm |
| title_short |
Load Balancing in Software Defined Networking using Round Robin Algorithm |
| title_full |
Load Balancing in Software Defined Networking using Round Robin Algorithm |
| title_fullStr |
Load Balancing in Software Defined Networking using Round Robin Algorithm |
| title_full_unstemmed |
Load Balancing in Software Defined Networking using Round Robin Algorithm |
| title_sort |
load balancing in software defined networking using round robin algorithm |
| publishDate |
2025 |
| url |
https://scholar.dlu.edu.vn/handle/123456789/4981 |
| _version_ |
1845408534420783104 |
| spelling |
oai:scholar.dlu.edu.vn:123456789-49812025-07-13T03:41:38Z Load Balancing in Software Defined Networking using Round Robin Algorithm Trần, Vĩnh Phúc Trương, Công Thành Đặng, Đăng Nguyên Vũ, Duy Hoàng Software-Defined Networking, Load Balancing, Round Robin, Mininet, ONOS, Tkinter, Network Visualization, Real-Time Monitoring. Software-Defined Networking (SDN) facilitates flexible network management by decoupling the control plane from the data plane, enabling centralized programmability. This paper presents a practical implementation of a load balancing system based on the Round Robin algorithm, developed for experimental and educational purposes in an SDN testbed using Mininet and the ONOS controller. The proposed setup involves a set of clients and servers interconnected through OpenFlow switches, with a standalone load balancer—deployed externally from the controller—sequentially forwarding traffic to available servers. A custom monitoring dashboard, built with Python and Tkinter, provides real-time visualization of network parameters including bandwidth, throughput, server load, and packet loss. Results from test scenarios show that the system achieves stable traffic distribution and effective resource utilization under varying network conditions. The work demonstrates the viability of lightweight traffic management strategies in SDN environments and serves as a baseline for further enhancements toward adaptive or intelligent control techniques. 2025-07-13T03:39:23Z 2025-07-13T03:39:23Z 2025-07-04 Conference paper Bài báo đăng trên KYHT trong nước (có ISBN) https://scholar.dlu.edu.vn/handle/123456789/4981 vi Hội thảo ICT 2025 [1] 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, Mar. 2008. [2] Mininet Project, “Mininet: An Instant Virtual Network on Your Laptop (or other PC),” [Online]. Available: https://mininet.org. [Accessed: March 2025]. [3] ONOS Project, “ONOS: Open Network Operating System,” [Online]. Available: https://onosproject.org. [Accessed: May 2025]. [4] Python Software Foundation, “Python 3.12 Documentation,” [Online]. Available: https://docs.python.org/3.12/. [Accessed: Ảpril 2025]. [5] Tkinter Documentation, “Graphical User Interfaces with Tk,” Python Software Foundation, [Online]. Available: https://docs.python.org/3/library/tkinter.html. [Accessed: May 2025]. [6] J. Postel, “Transmission Control Protocol,” RFC 793, Internet Engineering Task Force (IETF), Sept. 1981. [Online]. Available: https://tools.ietf.org/html/rfc793. [Accessed: May 2025]. [7] Wireshark Foundation, “Wireshark Network Protocol Analyzer,” [Online]. Available: https://www.wireshark.org. [Accessed: May 2025]. [8] C. E. Hopps, “Routing Information Protocol,” RFC 2453, IETF, Nov. 1998. [Online]. Available: https://tools.ietf.org/html/rfc2453. [Accessed: May 2025]. [9] J. Smith, "Round Robin Scheduling Algorithm," Journal of Computer Science, vol. 10, no. 2, pp. 123–130, 2019. [10] L. Peterson and B. Davie, Computer Networks: A Systems Approach, 5th ed. Morgan Kaufmann, 2011. [11] V. Paxson, “Bro: A system for detecting network intruders in real-time,” Computer Networks, vol. 31, no. 23–24, pp. 2435–2463, 1999. [12] R. Kurose and K. Ross, Computer Networking: A Top-Down Approach, 8th ed. Pearson, 2021. [13] iperf3 Project, “iperf - The ultimate speed test tool for TCP, UDP and SCTP,” [Online]. Available: https://iperf.fr. [Accessed: April 2025]. [14] L. Mamatas, I. Psaras, and G. Pavlou, “Distributed Load Balancing through Flow Relocation and Consolidation,” in Proc. IEEE ICC, 2012, pp. 1355–1359. [15] D. Kreutz, F. Ramos, P. Verissimo, C. Rothenberg, S. Azodolmolky, and S. Uhlig, “Software-Defined Networking: A Comprehensive Survey,” Proc. IEEE, vol. 103, no. 1, pp. 14–76, Jan. 2015. [16] M. Al-Fares, A. Loukissas, and A. Vahdat, “A Scalable, Commodity Data Center Network Architecture,” in Proc. ACM SIGCOMM, 2008, pp. 63–74. [17] H. Ballani, P. Costa, T. Karagiannis, and A. Rowstron, “Towards Predictable Datacenter Networks,” in Proc. ACM SIGCOMM, 2011, pp. 242–253. [18] M. Yu, J. Rexford, M. J. Freedman, and J. Wang, “Scalable Flow-Based Networking with DIFANE,” in Proc. ACM SIGCOMM, 2010, pp. 351–362. |