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Modelling IoT devices communication employing representative operation modes to reveal traffic generation characteristics

Modelling IoT devices communication employing representative operation modes to reveal traffic generation characteristics

Barakat, Basel ORCID: 0000-0001-9126-7613, Keates, Simeon ORCID: 0000-0002-2826-672X, Wassell, Ian J. and Arshad, Kamran (2019) Modelling IoT devices communication employing representative operation modes to reveal traffic generation characteristics. International Journal of Parallel, Emergent and Distributed Systems. ISSN 1744-5760 (Print), 1744-5779 (Online) (doi:https://doi.org/10.1080/17445760.2019.1649402)

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Abstract

Several traffic models for the Internet of Things (IoT) have been proposed in the literature. However, they can be considered as heuristic models since they only reflect the stochastic characteristic of the generated traffic. In this paper, we propose a model to represent the communication of IoT devices. The model was used to obtain the traffic generated by the devices. Therefore, the proposed model is able to capture a wider understanding of device behaviour than existing, state-of-the-art traffic models. The proposed model illustrates the behaviour of Machine-to-Machine uplink communication in a network with multiple-access limited information capacity shared channels. In this paper, we analysed the number of transmitted packets using the traffic model extracted from our proposed communication model and compared it with the state-of-the-art traffic models using simulations. The simulation results show that the proposed model has significantly higher accuracy in estimating the number of transmitted packets compared with the current models in the literature.

Item Type: Article
Uncontrolled Keywords: internet of things communication, communication system traffic, traffic model, stochastic process
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Department of Engineering Science
Faculty of Engineering & Science > Future Technology and the Internet of Things
Last Modified: 02 Oct 2019 15:30
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/24803

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