Clustering Internet of Things: A Review

Author:

Sholla Sahil,Kaur Sukhkirandeep,Begh Gh Rasool,Mir Roohie Naaz,Chishti M Ahsan

Abstract

Internet of Things is a paradigm shift in networking that seeks to connect virtually all things on the planet. Given the constrained nature of smart devices, energy efficient routing would play a key role in successful deployment of such networks. Clustering algorithms organize nodes of a network into groups or clusters and a specific designated node, cluster head is responsible for its cluster. Clustering algorithms have been particularly suggested in the context of Wireless Sensor Networks (WSN) but their application may also address similar challenges in Internet of Things (IoT). Clustering would facilitate energy efficient routing and topology management by delegating large chunk of communication overhead to cluster head. This paper presents a review of various clustering algorithms, analyses routing characteristics of various IoT domains and suggests appropriate clustering algorithms for each domain.

Publisher

The University of Danang

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Optimized Clustering and Routing with Sink Mobility for Enhanced Lifetime in IoT-based Wireless Sensor Networks for Smart Farming;2024 3rd International Conference on Artificial Intelligence For Internet of Things (AIIoT);2024-05-03

2. Driving Efficiency in Industry IoT: A Framework Powered by Intelligent Computing and Machine Learning;International Journal of Advanced Research in Science, Communication and Technology;2024-02-29

3. A review on WSN clustering algorithms in loT based applications;2023 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES);2023-04-28

4. A Role of Hierarchical Clustering Algorithms in Wireless Sensor Networks -A Review;2023 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES);2023-04-28

5. An Effective Approach of IIoT for Anomaly Detection Using Unsupervised Machine Learning Approach;Journal of ISMAC;2022-09-08

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3