A Scenario Based Approach for Context Query Generation

IoT hardware and application silos have achieved a significant progress in recent years. Yet, they have been unable to realize the full IoT potential, due to the lack of middleware platforms that provide horizontal IoT context sharing and integration. Context Management Platforms (CMPs) enable interoperability between IoT silos, and they provide Context-as- a-Service. CMPs enable real-time context-awareness but often lack appropriate mechanisms to support the evaluation of their performance. This paper proposes a novel scenario-based approach for generating context queries that can be used to assess the performance of a CMP, specifically the caching performance. The proposed approach allows a user to generate realistic context queries based on simulated scenarios. The proposed model has the ability to capture the real-world scenarios and translate them into a sequence of scenes. An ontology-based approach is used for scene modelling. Once the scenes are modelled, the situations are inferred through contextual reasoning. The proposed model reveals that inclusion of context information in the scene makes it feasible to handle uncertainty of situations as expected in the real-world. Based on the situations, context queries are generated using different query templates. To support a fair evaluation of the caching mechanism of a CMP, queries with different complexities are generated from the proposed model.