Today, the edge-cloud computing paradigm starts to gain increasing popularity, aiming to enable short latency, fast decision-making and intelligence at the network edge, especially for industrial applications. The container-based virtualization technology has been put on the roadmap by the industry to implement edge-cloud computing infrastructures. Has the performance of the container-based edge-cloud computing stacks reached industry requirement? In this paper, from the industrial client perspective, we provide a performance evaluation methodology and apply it to the state-of-the-art containerization-based edge-cloud computing infrastructures. The influences of the message sending interval, payload, network bandwidth and concurrent devices on full stack latency are measured, and the processing capability of executing machine learning tasks are benchmarked. The results show that containerization on the edge does not introduce noticeable performance degradation in terms of communication, computing and intelligence capabilities, making it a promising technology for the edge-cloud computing paradigm. However, there is a large room for performance improvement between current implementation of the edge-cloud infrastructure and the demanding requirements anticipated by time-critical industrial applications. We also emphasize and showcase that partitioning of an industrial application into microservices throughout the whole stack can be considered during solution design. The proposed evaluation methodology can be a reference to users of edge-cloud computing as well as developers to get a client perspective overview of system performance.

中文翻译：

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客户视角的边缘云计算堆栈中用于工业应用的容器化性能评估

如今，边缘云计算范例开始变得越来越流行，其目的是在网络边缘实现短延迟，快速决策和智能化，特别是对于工业应用。业界已将基于容器的虚拟化技术放在路线图上，以实现边缘云计算基础架构。基于容器的边缘云计算堆栈的性能是否达到行业要求？在本文中，从行业客户的角度出发，我们提供了一种性能评估方法，并将其应用于基于最新容器化的边缘云计算基础架构。测量了消息发送间隔，有效负载，网络带宽和并发设备对完整堆栈延迟的影响，并且对执行机器学习任务的处理能力进行了基准测试。结果表明，边缘容器化不会在通信，计算和智能功能方面引入明显的性能下降，使其成为边缘云计算范例的有希望的技术。但是，在边缘云基础架构的当前实施与时间紧迫的工业应用所预期的苛刻要求之间，仍有很大的性能提升空间。我们还强调并展示了在解决方案设计期间可以考虑将工业应用程序划分为整个堆栈中的微服务。