Faas‐sim: a trace‐driven simulation framework for serverless edge computing platforms
This paper presents faas-sim, a simulation framework tailored to serverless edge computing platforms. In serverless computing, platform operators are tasked with efficiently managing distributed computing infrastructure completely abstracted from application developers. To that end, platform operato...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10230/70209 |
| Acceso en línea: | http://hdl.handle.net/10230/70209 http://dx.doi.org/10.1002/spe.3277 |
| Access Level: | acceso abierto |
| Palabra clave: | Co-simulation Edge-cloud continuum Serverless edge computing Simulation |
| Sumario: | This paper presents faas-sim, a simulation framework tailored to serverless edge computing platforms. In serverless computing, platform operators are tasked with efficiently managing distributed computing infrastructure completely abstracted from application developers. To that end, platform operators and researchers need tools to design, build, and evaluate resource management techniques that efficiently use of infrastructure while optimizing application performance. This challenge is exacerbated in edge computing scenarios, where, compared to cloud computing, there is a lack of reference architectures, design tools, or standardized benchmarks. faas-sim bridges this gap by providing (a) a generalized model of serverless systems that builds on the function-as-a-service abstraction, (b) a simulator that uses trace data from real-world edge computing testbeds and representative workloads, and (c) a network topology generator to model and simulate distributed and heterogeneous edge-cloud systems. We present the conceptual design, implementation, and a thorough evaluation of faas-sim. By running experiments on both real-world test beds and replicating them using faas-sim, we show that the simulator provides accurate results and reasonable simulation performance. We have profiled a wide range of edge computing infrastructure and workloads, focusing on typical edge computing scenarios such as edge AI inference or data processing. Moreover, we present several instances where we have successfully used faas-sim to either design, optimize, or evaluate serverless edge computing systems. |
|---|