Using automatic topology discovery to diagnose PROFINET networks

Due to an increasing degree of automation, industrial communication networks grow in complexity and become more vulnerable to errors. Therefore a reliable network diagnosis is getting more and more important. Although modern industrial communication networks, such as PROFINET, have basic diagnosis mechanisms, they do not cover complex error cases. Furthermore, our work shows that a diagnosis of most error cases requires an automatic detection of a network's topology. In general, PROFINET does support topology discovery by providing the necessary protocols. However, implementing a reliable automatic topology discovery is not a trivial task e.g., because different vendors vary in their interpretation of the standards. This paper presents our approach for discovering the topology of a heterogeneous network. Further, a first approach for using the topology discovery for a high-level PROFINET diagnosis is shown.