Name
Abstract | ||
|---|---|---|
Computer network research experiments can be broadly grouped in three categories: simulated, controlled, and real-world experiments. Simulation frameworks, experiment testbeds and measurement tools, respectively, are commonly used as the platforms for carrying out network experiments. In many cases, given the nature of computer network experiments, properly configuring these platforms is a complex and time-consuming task, which makes replicating and validating research results quite challenging. This complexity can be reduced by leveraging tools that enable experiment reproducibility. In this paper, we show how a recently proposed reproducibility tool called Popper facilitates the reproduction of networking experiments. In particular, we detail the steps taken to reproduce results in two published articles that rely on simulations. The outcome of this exercise is a generic workflow for carrying out network simulation experiments. In addition, we briefly present two additional Popper workflows for running experiments on controlled testbeds, as well as studies that gather real-world metrics (all code is publicly available on Github). We close by providing a list of lessons we learned throughout this process.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3322790.3330596 | Proceedings of the 2nd International Workshop on Practical Reproducible Evaluation of Computer Systems |
Keywords | DocType | ISBN |
network experiment simulation, popper, reproducible network experiments, software automation | Conference | 978-1-4503-6756-1 |
Citations | PageRank | References |
2 | 0.38 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrea David | 1 | 2 | 0.38 |
| Mariette Souppe | 2 | 2 | 0.38 |
| Ivo Jimenez | 3 | 18 | 3.76 |
| Katia Obraczka | 4 | 2933 | 328.52 |
| Sam Mansfield | 5 | 2 | 0.38 |
| Kerry Veenstra | 6 | 16 | 4.06 |
| Carlos Maltzahn | 7 | 1201 | 87.49 |