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Article

An Effective Semantic Event Matching System in the Internet of Things (IoT) Environment

Information Systems Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia
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Sensors 2017, 17(9), 2014; https://doi.org/10.3390/s17092014
Received: 31 July 2017 / Revised: 28 August 2017 / Accepted: 30 August 2017 / Published: 2 September 2017
(This article belongs to the Special Issue Crowd-Sensing and Remote Sensing Technologies for Smart Cities)
IoT sensors use the publish/subscribe model for communication to benefit from its decoupled nature with respect to space, time, and synchronization. Because of the heterogeneity of communicating parties, semantic decoupling is added as a fourth dimension. The added semantic decoupling complicates the matching process and reduces its efficiency. Our proposed algorithm clusters subscriptions and events according to topic and performs the matching process within these clusters, which increases the throughput by reducing the matching time from the range of 16–18 ms to 2–4 ms. Moreover, the accuracy of matching is improved when subscriptions must be fully approximated, as demonstrated by an over 40% increase in F-score results. This work shows the benefit of clustering, as well as the improvement in the matching accuracy and efficiency achieved using this approach. View Full-Text
Keywords: publish/subscribe; semantic; event matching; IoT publish/subscribe; semantic; event matching; IoT
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MDPI and ACS Style

Alhakbani, N.; Hassan, M.M.; Ykhlef, M. An Effective Semantic Event Matching System in the Internet of Things (IoT) Environment. Sensors 2017, 17, 2014. https://doi.org/10.3390/s17092014

AMA Style

Alhakbani N, Hassan MM, Ykhlef M. An Effective Semantic Event Matching System in the Internet of Things (IoT) Environment. Sensors. 2017; 17(9):2014. https://doi.org/10.3390/s17092014

Chicago/Turabian Style

Alhakbani, Noura, Mohammed Mehedi Hassan, and Mourad Ykhlef. 2017. "An Effective Semantic Event Matching System in the Internet of Things (IoT) Environment" Sensors 17, no. 9: 2014. https://doi.org/10.3390/s17092014

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