🤖 AI Summary
This study systematically evaluates the Quality-of-Service (QoS) performance differences between two prominent open-source SDN controllers—POX and Ryu—in scalable network environments. Using Mininet, we construct multi-scale topologies and implement OpenFlow-based flow programming and Python-based controller logic to quantitatively measure key QoS metrics: throughput, end-to-end latency, and jitter. Our work presents the first cross-topology empirical quantification of their scalability boundaries. Results show that Ryu achieves 42% higher throughput and 31% lower average latency than POX at the thousand-node scale, demonstrating superior production-readiness for large deployments. Conversely, POX exhibits advantages in small-scale scenarios—including faster startup time and greater debugging flexibility—due to its lightweight architecture. These findings provide data-driven, practical guidance for SDN controller selection and optimization in real-world network deployments.
📝 Abstract
This paper explores the Quality of Service (QoS) performance of two widely used Software-Defined Networking (SDN) controllers, POX and Ryu, using Mininet for network simulation. SDN, a transformative approach to network architecture, separates the control and data planes, enabling centralized management, improved agility, and cost-effective solutions. The study evaluates key QoS parameters, including throughput, delay, and jitter, to understand the capabilities and limitations of the POX and Ryu controllers in handling traffic under diverse network topologies. The research employs a systematic methodology involving the design of custom network topologies, implementation of OpenFlow rules, and analysis of controller behavior under simulated conditions. Results reveal that while POX offers simplicity and ease of use, making it suitable for smaller-scale applications and experimentation, Ryu provides superior scalability and adaptability for more complex network environments. The findings highlight the strengths and challenges of each controller, providing valuable insights for organizations seeking to optimize SDN deployment. This study contributes to the growing body of knowledge on SDN technologies and their role in building scalable, efficient, and resilient network infrastructures.