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

机译:用于物联网(IOT)环境中的语义智能数据的高效事件匹配系统

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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. (C) 2019 Elsevier B.V. All rights reserved.
机译:由于该模型提供了支持异构各方之间的通信,因此已被证明是最适合的通信模型(IOT)环境中最适合的内容(IOT)环境中最适合。标准或常见发布/订阅使用精确的模型将事件与订阅匹配。然而,在IOT环境中,由于环境和各种形式的智能数据的产生,完全匹配是一个极端要求。因此,必须考虑语义上类似的事件并将其返回到用户作为可能的匹配。但是,大约订阅的匹配事件是一个更复杂的任务,对匹配效率产生负面影响。我们所提出的算法,使用树结构(SMT)进行语义匹配,提供有效的通信来支持时间关键的应用程序。与先前工作中的指数时间相比,SMT在吞吐量方面实现了线性时间。将SMT与分类群体结合在F评分方面提高了效果,这是召回和结果的召回和精度的效果,特别是当100%的订阅时进行语义匹配。 (c)2019 Elsevier B.v.保留所有权利。

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