×
Home Current Archive Editorial board
Instructions for papers
For Authors Aim & Scope Contact
Review paper

THE SURVEY OF CLUSTER BASED DATA COLLECTION PROCESS FOR IOT ENABLED WIRELESS SENSOR NETWORK USING SEVERAL OPTIMIZATION TECHNIQUE

By
R. Abirami Orcid logo ,
R. Abirami

Erode Arts and Science College , Erode , India

K. Sathishkumar Orcid logo ,
K. Sathishkumar

Erode Arts and Science College , Erode , India

Liu Guanzhou Orcid logo ,
Liu Guanzhou

UCSI University , Kuala Lumpur , Malaysia

M. Ramalingam Orcid logo ,
M. Ramalingam

Gobi Arts & Science College , Gobichettipalayam , India

Wasim Ahmad Orcid logo ,
Wasim Ahmad

UCSI University , Kuala Lumpur , Malaysia

Ali Bostani Orcid logo
Ali Bostani

American University of Kuwait , Kuwait City , Kuwait

Abstract

Offers a detailed analysis of optimization algorithms and routing protocols are created to overcome the issues on energy efficiency with the Internet of Things (IoT) Enabled Wireless Sensor Networks (WSNs). The study analyses nature-based metaheuristic methods such as the Genetic Algorithms, Particle Swarm Optimization, Firefly Optimization, Gray Wolf Optimization and Water-Cycle Algorithms, and specialised protocols of clustering, routing and data aggregation. Both approaches address such important issues as poor cluster head selection, energy disproportion, data duplication, network overloading, and early node failure that affect network lifespan and performance adversely. The research examines the energy optimization achieved by these algorithms in the form of intelligent cluster arrangements, traffic conscious routing, task scheduling processes and data aggregations. Particular attention is focused on the resource constrained contexts in which it is not viable to swap batteries, such as smart agriculture and smart cities. The discussion shows that hybrid metaheuristic solutions with improved optimization solutions can do better in terms of meeting several goals such as minimizing energy usage, improving throughput, increasing the ratio of packets delivered and Quality of Service demands. This survey can supply useful information about the development of energy-saving solutions and define new tendencies in the optimization of IoT networks.

References

1.
Badiger VS, Ganashree TS. Data aggregation scheme for IOT based wireless sensor network through optimal clustering method. Measurement: Sensors. 2022 Dec 1;24:100538.
2.
Pushpalatha S, Shivaprakasha KS. Hybrid leader artificial ecosystem-based optimization mechanism for CH selection and routing. Journal of Internet Services and Information Security. 2025;15(3):95–110.
3.
Alshehri HS, Bajaber F. A cluster-based data aggregation in IoT sensor networks using the firefly optimization algorithm. Journal of Computer Networks and Communications. 2024:1–17.
4.
Riadhusin R, Selvaraj V, Rakesh N, Ganesan A, Harita U, Saxena AK. Interfacing IoT sensors with library energy management systems. Indian Journal of Information Sources and Services. 2025;15(3):113–121.
5.
Lv C, Long G. Energy-efficient cluster head selection in Internet of Things networks using an optimized evaporation rate water-cycle algorithm. Journal of Engineering and Applied Science. 2025 Dec;72(1):34.

Citation

This is an open access article distributed under the  Creative Commons Attribution Non-Commercial License (CC BY-NC) License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 

Article metrics

Google scholar: See link

The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.