Fidelity-aware large-scale distributed network emulation

Abstract

The design and development of new network protocols, architectures, and technologies requires an evaluation phase where the researcher must provide empirical evidence for the performance of their contributions, potentially in comparison to existing solutions. In this context, network emulation has proven to be an attractive approach as it offers more flexibility compared to traditional testing platforms, and more realism compared to simulation. Network emulators provide contained, customisable, and scalable testing environments both for researchers to evaluate their contributions and for the community to reproduce their results. However, two limitations to network emulation have been identified and well documented in the literature: its scalability limits and its accuracy issues. This paper11This journal paper is an extension of a shorter paper (Elbouanani et al., 2023 [1]) previously presented in the TASIR (Testbeds for Advanced Systems Implementation and Research) workshop of Comsnets 2023 conference, and published in its proceedings. documents our attempts to address these concerns. Our findings are distilled into Hifinet: a lightweight scalable and fidelity-aware distributed network emulator. We particularly show how Hifinet outperforms its state-of-the-art counterparts in terms of scalability and efficiency by working around the flaws of their design principles and the technological limitations of the tools they rely on. Hifinet is also fidelity-enhanced, in that it implements a well-theorised fidelity monitoring framework, which passively monitors emulated packet delays to evaluate realism of network emulation and accuracy of results. Another asset of Hifinet is its ability to infer underlying causes in case of erroneous emulation and guide the user through fixing them. This is achieved by using delay tomography algorithms and heuristics.