Utilising Kronecker Algebra to Detect Unexpected Behaviour in Distributed Systems

P. Denzler, Johann Blieberger, W. Kastner
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Abstract

Current industrial trends require flexible and reconfigurable manufacturing systems, with Cyber-Physical Production Systems (CPPS) playing a crucial role. However, the increased flexibility and decentralisation increase the risk of unexpected or emerging system behaviour. Message sequence charts (MSCs) have proven helpful in the early stages of system design to capture intended scenarios. This paper introduces a process that utilises MSCs to identify unexpected system behaviour. After synthesising the MSCs into finite state machines, the process suggests applying Kronecker algebra to verify intended and identify unintended scenarios. The process is illustrated by an example depicting an auto-lock mechanism. The paper concludes by outlining further research focusing on implementing the process and identifying emergence at runtime.
利用Kronecker代数检测分布式系统中的意外行为
当前的工业趋势需要灵活和可重构的制造系统,其中网络物理生产系统(CPPS)发挥着至关重要的作用。然而,增加的灵活性和分散化增加了意外或新出现的系统行为的风险。消息序列图(MSCs)已被证明在系统设计的早期阶段对捕获预期场景很有帮助。本文介绍了一个利用msc识别意外系统行为的过程。在将MSCs合成为有限状态机之后,该过程建议应用Kronecker代数来验证预期和识别非预期场景。通过一个描述自动锁定机制的示例来说明该过程。本文最后概述了进一步的研究,重点是实现过程和识别运行时的出现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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