Open Access

ARTICLE

Energy Efficient Cluster-Based Optimal Resource Management in IoT Environment

J. V. Anchitaalagammai¹, T. Jayasankar^2,*, P. Selvaraj³, Mohamed Yacin Sikkandar⁴, M. Zakarya^5,6, Mohamed Elhoseny⁷, K. Shankar⁸

1 Department of Computer Science and Engineering, Velammal College of Engineering and Technology, Madurai, 625009, India
2 Department of Electronics and Communication Engineering, University College of Engineering, BIT Campus, Anna University, Tiruchirappalli, 620024, India
3 Department of Information Technology, SRM Institute of Science and Technology, Kattankulathur, 603203, Tamil Nadu, India
4 Department of Medical Equipment Technology, College of Applied Medical Sciences, Majmaah University, Al Majmaah, 11952, Saudi Arabia
5 Department of Mathematics, College of Science, King Khalid University, P.O. Box 9004, Abha, 61413, Saudi Arabia
6 Department of Mathematics, Faculty of Science, Al-Azhar University, Assiut, 71524, Egypt
7 College of Computer Information Technology, American University in the Emirates, Dubai, 503000, United Arab Emirates
8 Department of Computer Applications, Alagappa University, Karaikudi, India

* Corresponding Author: T. Jayasankar. Email:

Computers, Materials & Continua 2022, 70(1), 1247-1261. https://doi.org/10.32604/cmc.2022.017910

Received 17 February 2021; Accepted 02 May 2021; Issue published 07 September 2021

Abstract

Internet of Things (IoT) is a technological revolution that redefined communication and computation of modern era. IoT generally refers to a network of gadgets linked via wireless network and communicates via internet. Resource management, especially energy management, is a critical issue when designing IoT devices. Several studies reported that clustering and routing are energy efficient solutions for optimal management of resources in IoT environment. In this point of view, the current study devises a new Energy-Efficient Clustering-based Routing technique for Resource Management i.e., EECBRM in IoT environment. The proposed EECBRM model has three stages namely, fuzzy logic-based clustering, Lion Whale Optimization with Tumbling (LWOT)-based routing and cluster maintenance phase. The proposed EECBRM model was validated through a series of experiments and the results were verified under several aspects. EECBRM model was compared with existing methods in terms of energy efficiency, delay, number of data transmission, and network lifetime. When simulated, in comparison with other methods, EECBRM model yielded excellent results in a significant manner. Thus, the efficiency of the proposed model is established.

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