Open Access

ARTICLE

Energy Efficient Unequal Fault Tolerance Clustering Approach

Sowjanya Ramisetty^1,2, Divya Anand², Kavita^3,*, Sahil Verma³, NZ Jhanjhi⁴, Mehedi Masud⁵, Mohammed Baz⁶

1 Department of Computer Science and Engineering, KG Reddy College of Engineering and Technology, Hyderabad, India
2 School of Computer Science and Engineering, Lovely Professional University, Phagwara, India
3 Department of Computer Science and Engineering, Chandigarh University, Mohali, India
4 Department of Computer Science and Engineering, Tailor’s University, Malaysia
5 Department of Computer Science, College of Computers and Information Technology, Taif University, Taif, 21944, Saudi Arabia
6 Department of Computer Engineering, College of Computer and Information Technology, Taif University, Taif, 21994, Saudi Arabia

* Corresponding Author: Kavita. Email:

Computer Systems Science and Engineering 2023, 45(2), 1971-1983. https://doi.org/10.32604/csse.2022.021924

Received 20 July 2021; Accepted 14 October 2021; Issue published 03 November 2022

Abstract

For achieving Energy-Efficiency in wireless sensor networks (WSNs), different schemes have been proposed which focuses only on reducing the energy consumption. A shortest path determines for the Base Station (BS), but fault tolerance and energy balancing gives equal importance for improving the network lifetime. For saving energy in WSNs, clustering is considered as one of the effective methods for Wireless Sensor Networks. Because of the excessive overload, more energy consumed by cluster heads (CHs) in a cluster based WSN to receive and aggregate the information from member sensor nodes and it leads to failure. For increasing the WSNs’ lifetime, the CHs selection has played a key role in energy consumption for sensor nodes. An Energy Efficient Unequal Fault Tolerant Clustering Approach (EEUFTC) is proposed for reducing the energy utilization through the intelligent methods like Particle Swarm Optimization (PSO). In this approach, an optimal Master Cluster Head (MCH)-Master data Aggregator (MDA), selection method is proposed which uses the fitness values and they evaluate based on the PSO for two optimal nodes in each cluster to act as Master Data Aggregator (MDA), and Master Cluster Head. The data from the cluster members collected by the chosen MCH exclusively and the MDA is used for collected data reception from MCH transmits to the BS. Thus, the MCH overhead reduces. During the heavy communication of data, overhead controls using the scheduling of Energy-Efficient Time Division Multiple Access(EE-TDMA). To describe the proposed method superiority based on various performance metrics, simulation and results are compared to the existing methods.

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Keywords

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