OPC UA通信模型的瓶颈识别与性能建模

Andreas Burger, H. Koziolek, Julius Rückert, Marie Platenius-Mohr, G. Stomberg
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引用次数: 18

摘要

OPC UA通信架构目前正在成为工业自动化系统的一个组成部分,用于控制复杂的生产过程,如发电或造纸。随着最近发布的pub/sub通信扩展,OPC UA现在也可以支持快速循环控制应用程序,但是OPC UA实现的瓶颈及其在资源受限的工业设备上的可扩展性尚未得到很好的理解。以前的OPC UA性能评估主要关注客户端/服务器往返时间或关注抖动,但没有探索资源瓶颈或创建预测性能模型。我们使用OPC UA客户机/服务器和pub/sub通信进行了广泛的性能测量,并创建了基于线性回归的CPU利用率预测模型,该模型可用于调整硬件环境。我们发现服务器CPU是OPC UA pub/sub通信的主要瓶颈,但在Raspberry Pi Zero上允许每秒高达40,000个信号的吞吐量。我们还发现,如果超过20个客户机访问单个服务器,客户机/服务器会话管理开销会严重影响性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bottleneck Identification and Performance Modeling of OPC UA Communication Models
The OPC UA communication architecture is currently becoming an integral part of industrial automation systems, which control complex production processes, such as electric power generation or paper production. With a recently released extension for pub/sub communication, OPC UA can now also support fast cyclic control applications, but the bottlenecks of OPC UA implementations and their scalability on resource-constrained industrial devices are not yet well understood. Former OPC UA performance evaluations mainly concerned client/server round-trip times or focused on jitter, but did not explore resource bottlenecks or create predictive performance models. We have carried out extensive performance measurements with OPC UA client/server and pub/sub communication and created a CPU utilization prediction model based on linear regression that can be used to size hardware environments. We found that the server CPU is the main bottleneck for OPC UA pub/sub communication, but allows a throughput of up to 40,000 signals per second on a Raspberry Pi Zero. We also found that the client/server session management overhead can severely impact performance, if more than 20 clients access a single server.
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