OWL 2 Reasoning To Detect Energy-Efficient Software Variants From Context

Runtime variability management of component-based software systems allows to consider the current context of a system for system configuration to achieve energy-efficiency. For optimizing the system configuration at runtime, the early recognition of situations apt to reconfiguration is an important task. To describe these situations on differing levels of detail and to allow their recognition even if only incomplete information is available, we employ the ontology language OWL 2 and the reasoning services defined for it. In this paper, we show that the relevant situations for optimizing the current system configuration can be modeled in the different OWL 2 profiles. We further provide a case study on the performance of state of the art OWL 2 reasoning systems for answering concept queries and conjunctive queries modeling the situations to be detected.

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