Redesigning Network Simulation, Emulation and Experimentation Testbeds with Asynchronous Rust

As large language models are trained on datacenters with tens of thousands of compute nodes and are quickly becoming parts of our daily routines, the need for a flexible, easy-to-use, and high-performance research testbed for simulating, emulating and experimenting with new network protocols has become more pressing and relevant than ever. Conventional packet-level simulators are, by their nature of discrete-event simulation, not scalable enough; yet traditional network emulation testbeds, such as Mininet, are also showing their age with respect to the flexibility of implementing new algorithms, ability to run arbitrary application workloads, scalability to a large number of nodes, as well as the freedom of expanding beyond a single cluster to span multiple geographically distributed regions.

In this talk, I will introduce three new testbeds that we designed and implemented over the past five years to reimagine network simulation, emulation, and experimentation from the ground up, with a focus on simplicity, composability, and flexibility. I will start by revisiting the classic problem of network discrete-event simulation, and advocate that a process-based design is a simpler, more scalable, and performant choice than the current event-based design. I will show two new discrete-event simulation frameworks, called ns.py and Days, built using Python and Rust respectively, and with modern development advances in generators, asynchronous programming, and stackless coroutines.  I will show that these frameworks outperformed all existing discrete-event simulators and performance estimators by up to three orders of magnitude. ns.py is already open source on GitHub, and Days will be open source soon at https://days.sh.

I next present Nextmini, a modern, next-generation, high-performance networking research testbed for network emulation and experimentation. Using Rust, it is designed from scratch to be as flexible as possible, accommodating a wider array of resource scheduling algorithms. Its design strikes an excellent balance between flexibility and performance, supporting both performant user-space emulation for maximum flexibility, as well as much higher kernel-level performance when users need such a performance boost. It is scalable to a larger number of nodes with ease in the same cluster, and can be easily expanded to span multiple geographically distributed datacenters. Nextmini will be available as open source soon at https://nextmini.org.