Edge-RT: OS Support for Controlled Latency in the Multi-Tenant, Real-Time Edge
Edge-RT: OS Support for Controlled Latency in the Multi-Tenant, Real-Time Edge
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DOI：
10.1109/rtss55097.2022.00011
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发表时间：
2022-12
期刊：
影响因子：
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通讯作者：
Wenyuan Shao;Bite Ye;Huachuan Wang;Gabriel Parmer;Yuxin Ren
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文献类型：
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作者：
Wenyuan Shao;Bite Ye;Huachuan Wang;Gabriel Parmer;Yuxin Ren
许多领域的嵌入式和实时设备越来越依赖于网络连接。卸载计算的能力鼓励成本，尺寸，重量和功耗（C-SWaP）优化，而网络上的协调有效地使系统能够感知其本地传感器之外的环境，并进行全球协作。这个承诺意义重大：自动驾驶汽车（AV）通过基础设施、工厂聚合数据进行全局优化以及功率受限设备利用卸载的推理任务相互协调。低延迟无线（例如，5G）技术与边缘云相结合，进一步推动了这些趋势。不幸的是，由于有限的资源、所需的高性能、多租户的安全性和实时延迟的挑战性组合，边缘计算带来了重大挑战。本文介绍了Edge-RT，这是一组用于边缘的操作系统扩展，旨在满足跨计算链的端到端（数据包接收到传输）最后期限。它通过对每个客户端设备执行链来支持强大的安全性，从而隔离租户和设备计算。尽管它实际上注重截止日期和强隔离性，但它仍保持了高系统效率。为了做到这一点，Edge-RT专注于由对其进行操作的计算所继承的每个数据包的最后期限。它引入了避免每个数据包系统开销的机制，同时只对可预测调度产生有限的影响。结果表明，与Linux和EdgeOS相比，Edge-RT可以保持更高的吞吐量，并满足更多的截止日期，无论是在系统的双峰工作负载与利用率超过60%，在存在恶意任务，并作为系统在客户端扩展。
Embedded and real-time devices in many domains are increasingly dependent on network connectivity. The ability to offload computations encourages Cost, Size, Weight and Power (C-SWaP) optimizations, while coordination over the network effectively enables systems to sense the environment beyond their own local sensors, and to collaborate globally. The promise is significant: Autonomous Vehicles (AVs) coordinating with each other through infrastructure, factories aggregating data for global optimization, and power-constrained devices leveraging offloaded inference tasks. Low-latency wireless (e.g., 5G) technologies paired with the edge cloud, are further enabling these trends. Unfortunately, computation at the edge poses significant challenges due to the challenging combination of limited resources, required high performance, security due to multi-tenancy, and real-time latency. This paper introduces Edge-RT, a set of OS extensions for the edge designed to meet the end-to-end (packet reception to transmission) deadlines across chains of computations. It supports strong security by executing a chain per-client device, thus isolating tenant and device computations. Despite a practical focus on deadlines and strong isolation, it maintains high system efficiency. To do so, Edge-RT focuses on per-packet deadlines inherited by the computations that operate on it. It introduces mechanisms to avoid per-packet system overheads, while trading only bounded impacts on predictable scheduling. Results show that compared to Linux and EdgeOS, Edge-RT can both maintain higher throughput and meet significantly more deadlines both for systems with bimodal workloads with utilization above 60%, in the presence of malicious tasks, and as the system scales up in clients.