Evidence map›Paper›PMID 40445889›Full record

ArticlePloS one2025

Advance zonal rectangular low energy adaptive clustering hierarchy algorithm for optimal routing in wireless sensors network.

Fazia Akhtar, Ijaz Ahmed, Ahmed F Youssef, Idris H Smaili, Mohamed Mostafa Ramdan Ahmed, Ali M El-Rifaie

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Fazia AkhtarComputer Science Department, Federal Urdu University of Arts, Science and Technology, Islamabad, Pakistan.
Ijaz AhmedInterdisciplinary Research Center for Sustainable Energy Systems, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
Ahmed F YoussefCollege of Engineering and Technology, American University of the Middle East, Egaila, Kuwait.
Idris H SmailiDepartment of Electrical and Electronic Engineering, College of Engineering and Computer Science, Jazan University, Jazan, Saudi Arabia.
Mohamed Mostafa Ramdan AhmedDepartment of Electrical Technology, Faculty of Technology and Education, Helwan University, Cairo, Egypt.ORCID 0000-0002-2066-4256
Ali M El-RifaieCollege of Engineering and Technology, American University of the Middle East, Egaila, Kuwait.ORCID 0000-0003-1220-0053

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In wireless sensor networks (WSNs), power consumption is a recurring issue. Compared to other modern routing approaches that aim to reduce power consumption, cluster-based forwarding algorithms have been shown to be more energy efficient. Static clustering optimization is the main emphasis of this study on energy-efficient advanced zonal rectangular low energy adaptive clustering hierarchy (EE-AZR-LEACH) optimum routing, which takes a modern technique. To extend the lifespan of the cluster units and the system, we suggest using the multi-hopping approach. The proposed protocol significantly improves the network life time and energy efficiency of WSNs by optimizing static clustering and incorporating multi-hopping techniques. It can outperform existing protocols in power consumption, data transfer and stability, makes it a robust solution for large-scale and energy constrained environment. To help the Cluster Heads (CHs) with data transmission, EE-AZR-LEACH chose a Collaborator(CL) close to the central cluster. To increase the effectiveness of communication between the CHs located in the rectangular region and a central base station, these units took on the role of cluster leaders. The resilience, data transmission rate, power consumption, network endurance, and number of CHs of the system were clearly improved as a consequence. Our suggested routing system performs more effectively than AZR-LEACH, LEACH, MH-LEACH, and SEP in substantial areas. Furthermore, the proposed approach exhibits better convergence within 600 rounds when compared to AZR-LEACH, LEACH, MH-LEACH, and SEP. The findings indicate that after 1500 simulation cycles, the stability intervals for LEACH, MH-LEACH, SEP, and AZR-LEACH are 2.7%, 7.2%, 4.14%, and 5.34%, respectively. The simulation is run using MATLAB. The EE-AZR-LCH optimum routing, on the other hand, has a 6.8% survival rate. The MH-LEACH optimum routing has smaller total network tenure even if it provides a higher stability period than the EE-AZR-LEACH.

Indexed as

AlgorithmsComputer Communication NetworksWireless TechnologyCluster Analysis

Identifiers

PMID40445889
PMCPMC12124535

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.