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A Quality-of-Things Model for Assessing the Internet-of-Thing’s Non-Functional Properties

Qamar, A, Asim, M, Maamar, Z, Saeed, S and Baker, T (2019) A Quality-of-Things Model for Assessing the Internet-of-Thing’s Non-Functional Properties. Transactions on Emerging Telecommunications Technologies. ISSN 2161-3915

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Abstract

The Internet of Things (IoT) is in a “desperate” need for a practical model that would help in differentiating things according to their non-functional properties. Unfortunately, despite IoT growth, such properties either lack or ill-defined resulting into ad-hoc ways of selecting similar functional things. This paper discusses how things’ non-functional properties are combined into a Quality-of-Things (QoT) model. This model includes properties that define the performance of things’ duties related to sensing, actuating, and communicating. Since the values of QoT properties might not always be available or confirmed, providers of things can tentatively define these values and submit them to an Independent Regulatory Authority (IRA) whose role is to ensure fair competition among all providers. The IRA assesses the values of non-functional properties of things prior to recommending those that could satisfy users’ needs. To evaluate the technical doability of the QoT model, a set of comprehensive experiments are conducted using real datasets. The results depict an acceptable level of the QoT estimation accuracy.

Item Type: Article
Additional Information: This is the peer reviewed version of the following article: Qamar, A, Asim, M, Maamar, Z, Saeed, S, Baker, T. A Quality‐of‐Things model for assessing the Internet‐of‐Things' nonfunctional properties. Trans Emerging Tel Tech. 2019;e3668., which has been published in final form at https://dx.doi.org/10.1002/ett.3668. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science
Publisher: Wiley
Date Deposited: 21 May 2019 09:35
Last Modified: 07 Aug 2019 10:30
DOI or Identification number: 10.1002/ett.3668
URI: http://researchonline.ljmu.ac.uk/id/eprint/10738

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