A Service-Oriented Approach to Modeling and Reusing Event Correlations

In an IoT (Internet of Things) environment, event correlations may be dynamically interwoven because events usually span over many interrelated sensors. Our previous works used frequent sequence to measure the event correlations and mined them from a statistical perspective. We also proposed a service hyperlink model to encapsulate the event correlations. With the service hyperlink model, we made a preliminary attempt to reuse valuable event correlations to facilitate IoT applications. To consummate our previous method, this paper refines it in reusing the correlations, and focuses on which event would most probably appear after a previous event has occurred. To effectively mine the event correlations, we extend the traditional motif mining algorithms by introducing time constraint. Moreover, we connect services by service hyperlinks (i.e., abstraction of event correlations) to form a directed graph. An event can be routed on this graph. We have applied our approach in anomaly warning in a coal power plant and made extensive experiments to verify the effectiveness of the approach.