FABRIC Testbed is an international infrastructure designed to support cuttingedge large-scale experimentation and research in multiple disciplines such as networking, cybersecurity, distributed computing systems and machine learning, among others. Pmacctd, on the other hand, is a versatile open-source set of tools which collects and analyses network traffic data. This Master’s Thesis investigates the integration of the pmacctd toolset into the FABRIC testbed, enabling enhanced network monitoring and experimentation. The goal of this project is to develop a comprehensive tutorial and series of experiments to demonstrate how pmacctd can be used within FABRIC. By creating a Jupyter Notebook that integrates both tools and automates the use of pmacctd using Python, this work offers an educational resource for computer science and engineering students, enabling them to gain hands-on experience in network monitoring, Python-based network topology creation, and network experimentation. The project covers detailed experiments on protocols and tools such as IPFIX, ICMP, and TCP/UDP, with a focus on providing practical, step-by-step examples. The results demonstrate the powerful capabilities of pmacctd when integrated with FABRIC, while also highlighting the challenges posed by the complexity of the tool. Ultimately, this thesis contributes a valuable resource for future students and researchers in network experimentation.
FABRIC Testbed is an international infrastructure designed to support cuttingedge large-scale experimentation and research in multiple disciplines such as networking, cybersecurity, distributed computing systems and machine learning, among others. Pmacctd, on the other hand, is a versatile open-source set of tools which collects and analyses network traffic data. This Master’s Thesis investigates the integration of the pmacctd toolset into the FABRIC testbed, enabling enhanced network monitoring and experimentation. The goal of this project is to develop a comprehensive tutorial and series of experiments to demonstrate how pmacctd can be used within FABRIC. By creating a Jupyter Notebook that integrates both tools and automates the use of pmacctd using Python, this work offers an educational resource for computer science and engineering students, enabling them to gain hands-on experience in network monitoring, Python-based network topology creation, and network experimentation. The project covers detailed experiments on protocols and tools such as IPFIX, ICMP, and TCP/UDP, with a focus on providing practical, step-by-step examples. The results demonstrate the powerful capabilities of pmacctd when integrated with FABRIC, while also highlighting the challenges posed by the complexity of the tool. Ultimately, this thesis contributes a valuable resource for future students and researchers in network experimentation. Read More
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