Abstract
Edge computing processes data near its source, reducing latency and enhancing security compared to traditional cloud computing while providing its benefits. This paper explores edge computing for migrating an existing safety-critical robotics use case from an onboard dedicated hardware solution. We propose an edge robotics architecture based on Linux, Docker containers, Kubernetes, and a local wireless area network based on the TTWiFi protocol. Inspired by previous work on real-time cloud, we complement the architecture with a resource management and orchestration layer to help Linux manage, and Kubernetes orchestrate the system-wide shared resources (e.g., caches, memory bandwidth, and network). Our architecture aims to ensure the fault-tolerant and predictable execution of robotic applications (e.g., path planning) on the edge while upper-bounding the end-to-end latency and ensuring the best possible quality of service without jeopardizing safety and security.
Abstract (translated)
本文探讨了在边缘计算中将现有安全性关键机器人应用从车载专用硬件解决方案迁移的过程。我们提出了一种基于Linux、Docker容器、Kubernetes和基于TTWiFi协议的本地无线局域网的边缘机器人架构。受到之前关于实时云工作的启发，我们在架构中补充了一个资源管理和服务器层，以帮助Linux管理，并让Kubernetes在整个系统范围内协调共享资源（例如缓存、内存带宽和网络）。我们的架构旨在在边缘确保机器人应用（如路径规划）的高容错性和可预测性，同时提高端到端延迟，同时确保最高服务质量，而不会危及安全和安全性。
URL
https://arxiv.org/abs/2406.14391
