Situation recognition for service management systems using OWL 2 reasoners

Dargie, Waltenegus; Eldora,; Méndez, Julián; Möbius, Christoph; Rybina, Kateryna; Thost, Veronika; Turhan, Anni-Yasmin

doi:10.1109/percomw.2013.6529452

Cited by 8 publications

(6 citation statements)

References 14 publications

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“…The goal of our approach is to achieve distributed situation recognition times in the range of milliseconds, as we showed in Franco da Silva et al (2016). Many approaches using ontologies are in the range of seconds to minutes, even without distribution Wang et al (2004); Dargie et al (2013). Using machine learning leads to similar limitations regarding latency Attard et al (2013).…”

Section: Related Work On Distributed Situation Recognitionmentioning

confidence: 99%

Situation-aware adaptation of choreographies—The DiStOPT approach

Hirmer

Breitenbücher²,

Gaudio³

et al. 2022

Front. Internet Things

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The rise of the IoT and Industry 4.0 has increased the complexity of collaborating business processes, i. e., choreographies, as more partners and assets are involved. However, maintaining and executing business choreographies are complex tasks. Moreover, enabling robust and reliable execution is important, as failures or delays cause high costs among partners. For example, manufacturing companies usually depend on different suppliers, and it is crucial to be up-to-date about possible delays in shipments as this leads to delays in the manufacturing of their products. In this case, a choreography needs to be designed and operated in a way that it can adapt to cope with such problems. This requires i) timely recognition and tamper-resistent logging of problems that occur at each involved partner, which are referred to as situations in the scope of this article, and ii) an approach for a timely adaptation of choreographies based on occurring situations. Therefore, in this article, we introduce DiStOPT, an approach to i) model and recognize situations in a distributed and timely manner, and ii) model and execute situation-aware choreographies based on the recognized situations. The contributions are evaluated in a manufacturing scenario and validated by a prototypical implementation.

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Section: Related Work On Distributed Situation Recognitionmentioning

confidence: 99%

Situation-aware adaptation of choreographies—The DiStOPT approach

Hirmer

Breitenbücher²,

Gaudio³

et al. 2022

Front. Internet Things

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“…Our initial studies [30,42,43] on situation recognition in the HAEC scenario using standard ontology languages (i.e., the profiles of the web ontology language OWL 2) have underlined that temporal information is fundamental for situation recognition and that the representation of fuzzy information is important as well. Situation descriptions often need to refer to different time points.…”

Section: Temporalizing Obda-based Context Recognitionmentioning

confidence: 99%

Semantic Technologies for Situation Awareness

et al. 2020

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The project “Semantic Technologies for Situation Awareness” was concerned with detecting certain critical situations from data obtained by observing a complex hard- and software system, in order to trigger actions that allow this system to save energy. The general idea was to formalize situations as ontology-mediated queries, but in order to express the relevant situations, both the employed ontology language and the query language had to be extended. In this paper we sketch the general approach and then concentrate on reporting the formal results obtained for reasoning in these extensions, but do not describe the application that triggered these extensions in detail.

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“…The current state of the system is then captured at runtime in an ABox, similarly to [2,7,8,12]. To recognize critical situations for the resource manager, we employ the answering of class and conjunctive queries.…”

Section: Situation Recognition By Standard Owl 2 El Reasoningmentioning

confidence: 99%

“…In the past, we studied situation recognition to achieve energyefficiency for different applications-by switching between software variants [8] and for service management systems [7]. While these studies were targeted more towards coarser adaptations and therefore explored which OWL 2 profiles to use, the study at hand investigates whether adaptations on the OS level can be supported by systems implementing logical reasoning at all.…”

Section: Situation Recognition By Standard Owl 2 El Reasoningmentioning

confidence: 99%

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Bridging the application knowledge gap

Hähnel

Méndez

Thost

et al. 2014

Proceedings of the 13th Workshop on Adaptive and Reflective Middleware

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Regarding energy efficiency, resource management in complex hard-and software systems that is based on the information typically available to the OS alone does not yield best results. Nevertheless, general-purpose resource management should stay independent of application-specific information.To resolve this dilemma, we propose a generic, ontologybased approach to resource scheduling that is context-aware and takes information of running applications into account. The central task here is to recognize situations that might necessitate an adaptation of resource scheduling. This task is performed by logical reasoning over OWL ontologies. Our initial study shows that current OWL 2 EL reasoner systems can perform recognition of exemplary situations relevant to resource management within 4 seconds.

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Situation recognition for service management systems using OWL 2 reasoners

Cited by 8 publications

References 14 publications

Situation-aware adaptation of choreographies—The DiStOPT approach

Situation-aware adaptation of choreographies—The DiStOPT approach

Semantic Technologies for Situation Awareness

Bridging the application knowledge gap

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