Open Access

ARTICLE

ETM-IoT: Energy-Aware Threshold Model for Heterogeneous Communication in the Internet of Things

A. Vijaya Krishna¹, A. Anny Leema^2,*

1 School of Computer Science and Engineering, VIT University, Vellore, Tamilnadu, India
2 School of Information Technology and Engineering, VIT University, Vellore, Tamilnadu, India

* Corresponding Author: A. Anny Leema. Email:

Computers, Materials & Continua 2022, 70(1), 1815-1827. https://doi.org/10.32604/cmc.2022.018455

Received 09 March 2021; Accepted 20 May 2021; Issue published 07 September 2021

Abstract

The internet of things (IoT) has a wide variety of applications, which in turn raises many challenging issues. IoT technology enables devices to closely monitor their environment, providing context-aware intelligence based on the real-time data collected by their sensor nodes. The IoT not only controls these devices but also monitors their user's behaviour. One of the major issues related to IoT is the need for an energy-efficient communication protocol which uses the heterogeneity and diversity of the objects connected through the internet. Minimizing energy consumption is a requirement for energy-constrained nodes and outsourced nodes. The IoT nodes deployed in different geographical regions typically have different energy levels. This paper focuses on creating an energy-efficient protocol for IoT which can deal with the clustering of nodes and the cluster head selection process. An energy threshold model is developed to select the appropriate cluster heads and also to ensure uniform distribution of energy to those heads and member nodes. The proposed model envisages an IoT network with three different types of nodes, described here as advanced, intermediate and normal nodes. Normal nodes are first-level nodes, which have the lowest energy use; intermediate nodes are second-level nodes, which have a medium energy requirement; and the advanced class are third-level nodes with the highest energy use. The simulation results demonstrate that the proposed algorithm outperforms other existing algorithms. In tests, it shows a 26% improvement in network lifetime compared with existing algorithms.

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Keywords

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