Optimization of clustering process in WSN with meta-heuristic techniques - a survey

Dharmanshu Raval, Gaurang Raval, S. Valiveti
{"title":"Optimization of clustering process in WSN with meta-heuristic techniques - a survey","authors":"Dharmanshu Raval, Gaurang Raval, S. Valiveti","doi":"10.1109/RAIT.2016.7507911","DOIUrl":null,"url":null,"abstract":"In a wireless sensor network deployed in remote area, because of no rechargeable energy source available, the network lifetime is critically dependent on how efficiently the energy resources are used. Clustering is powerful technique to use energy efficiently. Meta-heuristic methods can be applied for clustering. In this paper, different meta-heuristic methods are analyzed such as PSO, ACO, GA, HS, SA, and its pros and cons are discussed. Also, how those cons are removed in further enhanced versions and combinations of these methods are described with its performance comparison.","PeriodicalId":289216,"journal":{"name":"2016 3rd International Conference on Recent Advances in Information Technology (RAIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 3rd International Conference on Recent Advances in Information Technology (RAIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RAIT.2016.7507911","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In a wireless sensor network deployed in remote area, because of no rechargeable energy source available, the network lifetime is critically dependent on how efficiently the energy resources are used. Clustering is powerful technique to use energy efficiently. Meta-heuristic methods can be applied for clustering. In this paper, different meta-heuristic methods are analyzed such as PSO, ACO, GA, HS, SA, and its pros and cons are discussed. Also, how those cons are removed in further enhanced versions and combinations of these methods are described with its performance comparison.
基于元启发式技术的WSN聚类过程优化研究综述
在偏远地区部署的无线传感器网络中,由于没有可用的可充电能源,网络寿命严重依赖于能源的利用效率。聚类是一种有效利用能量的强大技术。元启发式方法可以应用于聚类。本文分析了不同的元启发式方法,如PSO、ACO、GA、HS、SA,并讨论了它们的优缺点。此外,还描述了在进一步增强的版本中如何消除这些缺点以及这些方法的组合,并对其进行了性能比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信