基于Firefly算法的无线传感器网络节点部署优化方法

Wei Liu, Pan Li, Z. Ye, Shuai Yang
{"title":"基于Firefly算法的无线传感器网络节点部署优化方法","authors":"Wei Liu, Pan Li, Z. Ye, Shuai Yang","doi":"10.1109/aict52120.2021.9628937","DOIUrl":null,"url":null,"abstract":"for making the deployment distribution of wireless sensor network nodes more uniform and improve coverage, this paper proposes a node deployment optimization method based on the firefly algorithm. Firstly, a mathematical model is established to randomly deploy wireless sensor network nodes in the target area, and then the node deployment optimization problem is interpreted as a mathematical issue of searching extreme value; Finally, firefly algorithm is used for optimizing the location of wireless sensor network nodes stochastically deployed in the specified place to obtain this maximum coverage and complete the deployment. Experimental simulation results show that compared with genetic algorithm and particle swarm optimization algorithm, firefly algorithm can better avoid sinking into local optimum and avoid premature convergence. Compared with other two algorithm, the firefly algorithm has a faster search speed, better performance, and better stability.","PeriodicalId":375013,"journal":{"name":"2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Node Deployment Optimization Method of Wireless Sensor Network Based on Firefly Algorithm\",\"authors\":\"Wei Liu, Pan Li, Z. Ye, Shuai Yang\",\"doi\":\"10.1109/aict52120.2021.9628937\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"for making the deployment distribution of wireless sensor network nodes more uniform and improve coverage, this paper proposes a node deployment optimization method based on the firefly algorithm. Firstly, a mathematical model is established to randomly deploy wireless sensor network nodes in the target area, and then the node deployment optimization problem is interpreted as a mathematical issue of searching extreme value; Finally, firefly algorithm is used for optimizing the location of wireless sensor network nodes stochastically deployed in the specified place to obtain this maximum coverage and complete the deployment. Experimental simulation results show that compared with genetic algorithm and particle swarm optimization algorithm, firefly algorithm can better avoid sinking into local optimum and avoid premature convergence. Compared with other two algorithm, the firefly algorithm has a faster search speed, better performance, and better stability.\",\"PeriodicalId\":375013,\"journal\":{\"name\":\"2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/aict52120.2021.9628937\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/aict52120.2021.9628937","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

为了使无线传感器网络节点的部署分布更加均匀,提高网络的覆盖率,本文提出了一种基于萤火虫算法的节点部署优化方法。首先建立了在目标区域随机部署无线传感器网络节点的数学模型,然后将节点部署优化问题解释为搜索极值的数学问题;最后,利用萤火虫算法对随机部署在指定地点的无线传感器网络节点进行位置优化,以获得该最大覆盖范围,完成部署。实验仿真结果表明,与遗传算法和粒子群优化算法相比,萤火虫算法能更好地避免陷入局部最优,避免过早收敛。与其他两种算法相比,萤火虫算法具有更快的搜索速度、更好的性能和更好的稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Node Deployment Optimization Method of Wireless Sensor Network Based on Firefly Algorithm
for making the deployment distribution of wireless sensor network nodes more uniform and improve coverage, this paper proposes a node deployment optimization method based on the firefly algorithm. Firstly, a mathematical model is established to randomly deploy wireless sensor network nodes in the target area, and then the node deployment optimization problem is interpreted as a mathematical issue of searching extreme value; Finally, firefly algorithm is used for optimizing the location of wireless sensor network nodes stochastically deployed in the specified place to obtain this maximum coverage and complete the deployment. Experimental simulation results show that compared with genetic algorithm and particle swarm optimization algorithm, firefly algorithm can better avoid sinking into local optimum and avoid premature convergence. Compared with other two algorithm, the firefly algorithm has a faster search speed, better performance, and better stability.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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