Open Access

ARTICLE

Distributed Multi-hop Clustering Approach with Low Energy Consumption in WSN

R. Nithya^1,*, Roobaea Alroobaea², Ahmed Binmahfoudh³, Zairi Ismael Rizman⁴

1 Department of Computer Science and Engineering, Vivekananda College of Engineering for Women, Tiruchengode, 637205, Tamil Nadu, India
2 Department of Computer Science, College of Computers and Information Technology, Taif University, P. O. Box 11099, Taif, 21944, Saudi Arabia
3 Department of Computer Engineering, College of Computers and Information Technology, Taif University, P. O. Box 11099, Taif, 21944, Saudi Arabia
4 School of Electrical Engineering, College of Engineering, Universiti Teknologi MARA, 23000, Dungun, Terengganu, Malaysia

* Corresponding Author: R. Nithya. Email:

Computer Systems Science and Engineering 2023, 45(1), 903-924. https://doi.org/10.32604/csse.2023.030749

Received 01 April 2022; Accepted 18 May 2022; Issue published 16 August 2022

Abstract

The purpose of sensing the environment and geographical positions, device monitoring, and information gathering are accomplished using Wireless Sensor Network (WSN), which is a non-dependent device consisting of a distinct collection of Sensor Node (SN). Thus, a clustering based on Energy Efficient (EE), one of the most crucial processes performed in WSN with distinct environments, is utilized. In order to efficiently manage energy allocation during sensing and communication, the present research on managing energy efficiency is performed on the basis of distributed algorithm. Multiples of EE methods were incapable of supporting EE routing with MIN-EC in WSN in spite of the focus of EE methods on energy harvesting and minimum Energy Consumption (EC). The three stages of performance are proposed in this research work. At the outset, during routing and Route Searching Time (RST) with fluctuating node density and PKTs, EC is reduced by the Hybrid Energy-based Multi-User Routing (HEMUR) model proposed in this work. Energy efficiency and an ideal route for various SNs with distinct PKTs in WSN are obtained by this model. By utilizing the Approximation Algorithm (AA), the Bregman Tensor Approximation Clustering (BTAC) is applied to improve the Route Path Selection (RPS) efficiency for Data Packet Transmission (DPT) at the Sink Node (SkN). The enhanced Network Throughput Rate (NTR) and low DPT Delay are provided by BTAC. To MAX the Clustering Efficiency (CE) and minimize the EC, the Energy Effective Distributed Multi-hop Clustering (GISEDC) method based on Generalized Iterative Scaling is implemented. The Multi-User Routing (MUR) is used by the HEMUR model to enhance the EC by 20% during routing. When compared with other advanced techniques, the Average Energy Per Packet (AEPP) is enhanced by 39% with the application of proportional fairness with Boltzmann Distribution (BD). The Gaussian Fast Linear Combinations (GFLC) with AA are applied by BTAC method with an enhanced Communication Overhead (COH) for an increase in performance by 19% and minimize the DPT delay by 23%. When compared with the rest of the advanced techniques, CE is enhanced by 8% and EC by 27% with the application of GISEDC method.

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Keywords

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