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Montazerolghaem, Ahmadreza, Imanpour, Somaye. (1404). Evaluation and Performance Analysis of the Ryu Controller in Various Network Scenarios. پژوهشنامه مدیریت اجرایی, 2(3), 1-17. doi: 10.22080/cste.2025.28843.1022
Ahmadreza Montazerolghaem; Somaye Imanpour. "Evaluation and Performance Analysis of the Ryu Controller in Various Network Scenarios". پژوهشنامه مدیریت اجرایی, 2, 3, 1404, 1-17. doi: 10.22080/cste.2025.28843.1022
Montazerolghaem, Ahmadreza, Imanpour, Somaye. (1404). 'Evaluation and Performance Analysis of the Ryu Controller in Various Network Scenarios', پژوهشنامه مدیریت اجرایی, 2(3), pp. 1-17. doi: 10.22080/cste.2025.28843.1022
Montazerolghaem, Ahmadreza, Imanpour, Somaye. Evaluation and Performance Analysis of the Ryu Controller in Various Network Scenarios. پژوهشنامه مدیریت اجرایی, 1404; 2(3): 1-17. doi: 10.22080/cste.2025.28843.1022

Evaluation and Performance Analysis of the Ryu Controller in Various Network Scenarios

Contributions of Science and Technology for Engineering
مقاله 4، دوره 2، شماره 3، مهر 2025، صفحه 1-17    اصل مقاله (861.36 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22080/cste.2025.28843.1022
نویسندگان
Ahmadreza Montazerolghaem* ؛ Somaye Imanpour
Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran
تاریخ دریافت: 25 اسفند 1403،  تاریخ بازنگری: 27 فروردین 1404،  تاریخ پذیرش: 15 اردیبهشت 1404 
چکیده
Software-defined networking represents a revolutionary shift in network technology by decoupling the data plane from the control plane. In this architecture, all network decision-making processes are centralized in a controller, meaning each switch receives routing information from the controller and forwards network packets accordingly. This clearly highlights the crucial role of controllers in SDN performance. Ryu is one of the widely used SDN controllers, known for its ease of use in research due to its support for Python programming. This makes Ryu a suitable option for experimental and academic studies. In this research, we evaluate the performance of the Ryu controller based on various network metrics and across different network topologies. For experimental analysis, we use Mininet, a powerful network emulation tool that enables the creation of diverse network structures and the connection of switches to controllers. To facilitate the experiments, we developed a Python based script that executes various network scenarios, connects to different controllers, and captures and stores the results. This study not only provides a comprehensive performance evaluation of the Ryu controller but also paves the way for evaluating other SDN controllers in future research.
کلیدواژه‌ها
Software-Defined Networking؛ Data Plane؛ Control Plane؛ Controller؛ Mininet؛ Ryu
مراجع
  1. Ryu project team, & Ryu, S. D. N. (2014). Framework-English Edition. RYU project team, https://ryu-sdn.org/.
  2. Albu-Salih, A. T. (2022). Performance Evaluation of Ryu Controller in Software Defined Networks. Journal of Al-Qadisiyah for Computer Science and Mathematics, 14(1), 1. doi:10.29304/jqcm.2022.14.1.879.
  3. Uddin, R., & Monir, F. (2021). Performance Evaluation of Ryu Controller with Weighted Round Robin Load Balancer. Cybersecurity in Emerging Digital Era. ICCEDE 2020. Communications in Computer and Information Science, vol 1436. Springer, Cham, Switzerland. doi:10.1007/978-3-030-84842-2_9.
  4. Bhardwaj, S., & Panda, S. N. (2022). Performance Evaluation Using RYU SDN Controller in Software-Defined Networking Environment. Wireless Personal Communications, 122(1), 701–723. doi:10.1007/s11277-021-08920-3.
  5. Islam, M. T., Islam, N., & Refat, M. Al. (2020). Node to Node Performance Evaluation through RYU SDN Controller. Wireless Personal Communications, 112(1), 555–570. doi:10.1007/s11277-020-07060-4.
  6. Alssaheli, O. M. A., Zainal Abidin, Z., Zakaria, N. A., & Abal Abas, Z. (2021). Implementation of network traffic monitoring using software defined networking Ryu controller. WSEAS Transactions on Systems and Control, 16, 270–277. doi:10.37394/23203.2021.16.23.
  7. Li, Y., Guo, X., Pang, X., Peng, B., Li, X., & Zhang, P. (2020). Performance Analysis of Floodlight and Ryu SDN Controllers under Mininet Simulator. 2020 IEEE/CIC International Conference on Communications in China, ICCC Workshops 2020, 85–90. doi:10.1109/ICCCWorkshops49972.2020.9209935.
  8. Ali, J., Lee, S., & Roh, B. (2018). Performance Analysis of POX and Ryu with Different SDN Topologies. Proceedings of the 2018 International Conference on Information Science and System, 244–249. doi:10.1145/3209914.3209931.
  9. Imanpour, S., Montazerolghaem, A., & Afshari, S. (2024). Simulanteous Load Balancing of Servers and Controllers in SDN-based IoMT. 15th International Conference on Information and Knowledge Technology, IKT 2024, 172–176. doi:10.1109/IKT65497.2024.10892775.
  10. Mahdizadeh, M., Montazerolghaem, A., & Jamshidi, K. (2024). Task scheduling and load balancing in SDN-based cloud computing: A review of relevant research. Journal of Engineering Research (Kuwait). doi:10.1016/j.jer.2024.11.002.
  11. Imanpour, S., Montazerolghaem, A., & Afshari, S. (2024). Load Balancing of Servers in Software-defined Internet of Multimedia Things using the Long Short-Term Memory Prediction Algorithm. 2024 10th International Conference on Web Research, ICWR 2024, 291–296. doi:10.1109/ICWR61162.2024.10533321.
  12. Imanpour, S., Kazemiesfeh, M., & Montazerolghaem, A. (2024). Multi-level threshold SDN controller dynamic load balancing. Proceeding of 8th International Conference on Smart Cities, Internet of Things and Applications, SCIoT 2024, 88–93. doi:10.1109/SCIoT62588.2024.10570100.
  13. Salehnia, T., Montazerolghaem, A., Mirjalili, S., Khayyambashi, M. R., & Abualigah, L. (2024). SDN-based optimal task scheduling method in Fog-IoT network using combination of AO and WOA. Handbook of Whale Optimization Algorithm, Academic Press, Cambridge, United States. doi:10.1016/b978-0-32-395365-8.00014-2.
  14. Imanpoura, S., Montazerolghaemb, A., & Afsharic, S. (2025). Optimizing Server Load Distribution in Multimedia IoT Environments through LSTM-Based Predictive Algorithms. International Journal of Web Research, 8(1), 61–77.. doi:22133/ijwr.2025.498457.1258.
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