Klonet: an Easy-to-Use and Scalable Platform for Computer Networks Education
Tie Ma, Long Luo, Hongfang Yu, Xi Chen, Jingzhao Xie, Chongxi Ma, Yunhan Xie, Gang Sun, Tianxi Wei, Li Chen, Yanwei Xu, Nicholas Zhang
Abstract
Currently, one of the simplest and most effective ways for people to gain an in-depth understanding of computer networks is through hands-on practice and experimentation on software platforms. While education is important for the field of computer networks, existing platforms are inadequate in usability and scalability, failing to fully meet all the teaching needs of computer networking education.
This paper describes our experiences in designing and using Klonet, an emulation platform for computer networking education. Klonet is easy-to-use for both students and tutors, which has been carefully designed to lower the barrier to use, thus making the practice more efficient. Klonet also demonstrates good scalability. It adopts a container-based distributed architecture and a virtual network embedding algorithm customized for this platform. Evaluation experiments show that Klonet exhibits better scalability, such as supporting more students with fewer hardware resources (i.e., servers) and deploying virtual network topologies more quickly. Furthermore, to ensure stability during teaching, Klonet enhances the robustness of its upper orchestrator and underlying virtual networks. So far, Klonet has been adopted in 3 universities and 4 courses, serving more than 800 students. We showcase Klonet's usefulness in networking education with real use cases, including a scenario with ∼10,000 emulated routers. We also share our lessons learned from the 4 years of Klonet development and 2 years of operations.
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