EdgeFaaSBench: Benchmarking Edge Devices Using Serverless Computing

Due to the development of small-size, energy-efficient, and powerful CPUs and GPUs for single board computers, various edge devices are widely adopted for hosting real-world applications, including real-time object detection, autonomous driving, and sensor stream processing. At the same time, serverless computing receives increasing attention as a new application deployment model because of its simplicity, scalability, event-driven processing, and short-lived computation. Therefore, there is a growing demand for applying serverless computing to edge computing environments. However, due to the lack of characterization of serverless edge computing (e.g., application performance and impact from resource heterogeneity), researchers and practitioners have to conduct tedious measurements to understand the performance of serverless applications on edge devices in non-systematic ways.We create EdgeFaaSBench, a novel benchmark suite for serverless computing on edge devices, to bridge this gap. EdgeFaaSBench is developed on top of Apache OpenFaaS with Docker Swarm and can run various serverless benchmark workloads on edge devices with different hardware specifications (e.g., GPUs). EdgeFaaSBench contains 14 different benchmark workloads running on heterogeneous edge devices and captures various system-level, application-level, and serverless-specific metrics, including system utilization, response time, cold/warm start times, and impact of concurrent function executions. Experimental studies are conducted on two widely used edge devices, Raspberry Pi 4B and Jetson Nano, to show EdgeFaaSBench’s capabilities to benchmark serverless computing on edge devices.