Sanahmadi, Arman, Abdolahi Azgomi, Mohammad and Goudarzi, Shidrokh ORCID: https://orcid.org/0000-0003-0383-3553 (2023) Modeling energy consumption in IoT systems using stochastic reward nets. Journal of Soft Computing and Information Technology (JSCIT), 11 (4). pp. 89-101. ISSN 2383-1006

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Abstract

Today, internet of things (IoT) is widely used in various fields, such as health control, smart city, smart
buildings, and so on. One of the severe concerns in IoT-based systems is the issue of energy consumption and its
management. The IoT-based systems have limited resources. It is also difficult to access them in many situations;
so, their energy sources must be appropriately consumed and managed. In order to design and build IoT systems,
many factors, such as the usable chips, the type of communication protocols, the timing of data transfer, and so
on, directly affect the system's energy consumption. Therefore, in the design phase of these systems, it is
necessary to model and evaluate their energy consumption and their compliance with the requirements. In this
paper, a stochastic reward nets (SRN) model is introduced for modeling and quantitative evaluation of energy
consumption in IoT-based systems. In this method, first the modeling of the energy source and the influencing
factors are explained, then the entire system is modeled using these basic models, Then, by changing the
configuration of the system, the influencing factors on energy consumption are studied and measured, and the
most suitable configuration is selected using the results. This method can lead to a significant reduction in the
costs of a system before its operation. Using this model, a case study has been investigated and the effects of
various factors, such as the number of nodes connected to the cluster head, the existence of sleep/wake mode,
and different transmission rates on system performance and energy consumption are investigated. In this paper
the effect of the system configuration on the amount of energy consumption has been evaluated and it has been
shown that the packet delay increases with the increase in the number of nodes connected to the cluster head, and
in order to reduce the number of packets in the buffer by 75% and reduce the end-to-end delay of the packets, a
transmitter with a transmission rate of 0.037 should be used.

Item Type:	Article
Keywords:	Internet of things power management modeling and evaluation stochastic reward nets
Subjects:	Computing
Depositing User:	Shidrokh Goudarzi
Date Deposited:	02 Dec 2024 08:36
Last Modified:	03 Dec 2024 15:15
URI:	https://repository.uwl.ac.uk/id/eprint/12940

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