Distributed localized contextual event reasoning under uncertainty

Kolomvatsos, K., Anagnostopoulos, C. and Hadjiefthymiades, S. (2016) Distributed localized contextual event reasoning under uncertainty. IEEE Internet of Things Journal, 4(1), pp. 183-191. (doi: 10.1109/JIOT.2016.2638119)

Abstract

We focus on Internet of Things (IoT) environments where sensing and computing devices (nodes) are responsible to observe, reason, report and react to a specific phenomenon. Each node captures context from data streams and reasons on the presence of an event. We propose a distributed predictive analytics scheme for localized context reasoning under uncertainty. Such reasoning is achieved through a contextualized, knowledge-driven clustering process, where the clusters of nodes are formed according to their belief on the presence of the phenomenon. Each cluster enhances its localized opinion about the presence of an event through consensus realized under the principles of Fuzzy Logic (FL). The proposed FLdriven consensus process is further enhanced with semantics adopting Type-2 Fuzzy Sets to handle the uncertainty related to the identification of an event. We provide a comprehensive experimental evaluation and comparison assessment with other schemes over real data and report on the benefits stemmed from its adoption in IoT environments.

• Item Type: Articles
• Additional Information: This work is funded by the European Commission (FIRE+ challenge, H2020) that aims to provide research, technological development and demonstration under the grant agreement no 645220 (RAWFIE).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Anagnostopoulos, Dr Christos and Kolomvatsos, Dr Kostas
• Authors: Kolomvatsos, K., Anagnostopoulos, C., and Hadjiefthymiades, S.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: IEEE Internet of Things Journal
• Publisher: IEEE
• ISSN: 2327-4662
• ISSN (Online): 2327-4662
• Published Online: 09 December 2016
• Copyright Holders: Copyright © 2016 IEEE
• First Published: First published in IEEE Internet of Things Journal 2016
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher