An efficient event matching system for semantic smart data in the Internet of Things (IoT) environment

Abstract The publish/subscribe model for communication has proved to be the most suitable in the Internet of things (IoT) environment because of the decoupling provided by this model that supports communication among heterogeneous parties. The standard or common publish/subscribe uses exact model to match events to subscriptions. However, in the IoT environment, an exact match is an extreme requirement because of the diverse and large environment and generation of various forms of Smart data. Therefore, semantically similar events must be considered and returned to subscribers as a possible match. However, matching events approximately to subscriptions is a much more complex task that negatively affects the efficiency of matching. Our proposed algorithm, semantic matching using the tree structure (SMT), provides efficient communication to support time-critical applications. SMT achieved linear time in terms of throughput compared with exponential time achieved in previous work. Combining SMT with taxonomy clustering improved the effectiveness in terms of the F-score, which is an indication of the recall and precision of the results, particularly when 100% of subscriptions were to be semantically matched.