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Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

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

Barakat, Basel, Keates, Simeon, 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, 36 (2). pp. 117-129. ISSN 1744-5760

Item Type: Article


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.

24803 BARAKAT_Modelling_IoT_Devices_Communication_(AAM)_2019.pdf - Accepted Version
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Depositing User: Basel Barakat


Item ID: 14168
Identification Number:
ISSN: 1744-5760
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Users with ORCIDS

ORCID for Basel Barakat: ORCID iD

Catalogue record

Date Deposited: 25 Nov 2021 13:59
Last Modified: 25 Jan 2022 08:49


Author: Basel Barakat ORCID iD
Author: Simeon Keates
Author: Ian J. Wassell
Author: Kamran Arshad

University Divisions

Faculty of Technology > School of Computer Science



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