Open Access

ARTICLE

Adaptive Route Sink Relocation Using Cluster Head Chain Cycling Model in WSN

M. Sudha^1,*, P. Shanmugapriya², Rami Q. Malik³, Ahmed Alkhayyat⁴

1 Department of Electronics and Communication Engineering, Paavai Engineering College, Namakkal, 637018, India
2 Department of Electronics and Communication Engineering, Saranathan College of Engineering, Tiruchirappalli, 620012, India
3 Department of Medical Instrumentation Techniques Engineering, Al-Mustaqbal University College, Hillah, 51001, Iraq
4 College of Technical Engineering, The Islamic University, Najaf, Iraq

* Corresponding Author: M. Sudha. Email:

Intelligent Automation & Soft Computing 2023, 36(2), 1811-1826. https://doi.org/10.32604/iasc.2023.032265

Received 12 May 2022; Accepted 30 June 2022; Issue published 05 January 2023

Abstract

Wireless Sensor Networks (WSN) have revolutionized the processes involved in industrial communication. However, the most important challenge faced by WSN sensors is the presence of limited energy. Multiple research investigations have been conducted so far on how to prolong the energy in WSN. This phenomenon is a result of inability of the network to have battery powered-sensor terminal. Energy-efficient routing on packet flow is a parallel phenomenon to delay nature, whereas the primary energy gets wasted as a result of WSN holes. Energy holes are present in the vicinity of sink and it is an important efficient-routing protocol for WSNs. In order to solve the issues discussed above, an energy-efficient routing protocol is proposed in this study named as Adaptive Route Decision Sink Relocation Protocol using Cluster Head Chain Cycling approach (ARDSR-CHC2H). The proposed method aims at improved communication at sink-inviting routes. At this point, Cluster Head Node (CHN) is selected, since it consumes low energy and permits one node to communicate with others in two groups. The main purpose of the proposed model is to reduce energy consumption and define new interchange technology. A comparison of simulation results demonstrates that the proposed algorithm achieved low cluster creation time, better network error and high Packet Delivery Rate with less network failure.

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Keywords

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