基于遗传算法的移动无线自组网节点移动策略

Qi Wan, Bingqing Han
{"title":"基于遗传算法的移动无线自组网节点移动策略","authors":"Qi Wan, Bingqing Han","doi":"10.1109/ISCEIC53685.2021.00017","DOIUrl":null,"url":null,"abstract":"Mobility is the most distinctive and important feature of Mobile Wireless Ad Hoc Networks(MANET), which brings many limitations along with its wide applications. A good mobility model is a good basis for further improving the performance of routing layer and MAC layer. Therefore, a movement strategy is proposed for the node movement problem. Only those nodes that are poorly distributed and meet the conditions are selected to form the set of mobile nodes. Neighborhood distribution information and residual energy information are fully considered for improving the initial population and fitness function of the genetic algorithm. Then, the improved genetic algorithm is used to search for the optimal next mobile position for each node in the set. The simulation results show that the nodes in the network can achieve higher network coverage and connectivity with fewer moves, regardless of whether the nodes are well or poorly distributed.","PeriodicalId":342968,"journal":{"name":"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mobile Strategy for Nodes in Mobile Wireless Ad Hoc Networks Based on Genetic Algorithm\",\"authors\":\"Qi Wan, Bingqing Han\",\"doi\":\"10.1109/ISCEIC53685.2021.00017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobility is the most distinctive and important feature of Mobile Wireless Ad Hoc Networks(MANET), which brings many limitations along with its wide applications. A good mobility model is a good basis for further improving the performance of routing layer and MAC layer. Therefore, a movement strategy is proposed for the node movement problem. Only those nodes that are poorly distributed and meet the conditions are selected to form the set of mobile nodes. Neighborhood distribution information and residual energy information are fully considered for improving the initial population and fitness function of the genetic algorithm. Then, the improved genetic algorithm is used to search for the optimal next mobile position for each node in the set. The simulation results show that the nodes in the network can achieve higher network coverage and connectivity with fewer moves, regardless of whether the nodes are well or poorly distributed.\",\"PeriodicalId\":342968,\"journal\":{\"name\":\"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCEIC53685.2021.00017\",\"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 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCEIC53685.2021.00017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

移动性是移动无线自组网(MANET)最显著和最重要的特点,但在其广泛应用的同时也带来了许多局限性。良好的迁移模型是进一步提高路由层和MAC层性能的良好基础。因此,针对节点移动问题,提出了一种移动策略。只选取分布较差且满足条件的节点构成移动节点集。为了改进遗传算法的初始种群和适应度函数,充分考虑了邻域分布信息和剩余能量信息。然后,使用改进的遗传算法对集合中的每个节点搜索下一个最优移动位置。仿真结果表明,无论节点分布好坏,网络中的节点都可以通过更少的移动实现更高的网络覆盖率和连通性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Mobile Strategy for Nodes in Mobile Wireless Ad Hoc Networks Based on Genetic Algorithm
Mobility is the most distinctive and important feature of Mobile Wireless Ad Hoc Networks(MANET), which brings many limitations along with its wide applications. A good mobility model is a good basis for further improving the performance of routing layer and MAC layer. Therefore, a movement strategy is proposed for the node movement problem. Only those nodes that are poorly distributed and meet the conditions are selected to form the set of mobile nodes. Neighborhood distribution information and residual energy information are fully considered for improving the initial population and fitness function of the genetic algorithm. Then, the improved genetic algorithm is used to search for the optimal next mobile position for each node in the set. The simulation results show that the nodes in the network can achieve higher network coverage and connectivity with fewer moves, regardless of whether the nodes are well or poorly distributed.
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
期刊最新文献
Research on the Mechanical Zero Position Capture and Transfer of Steering Gear Based on Machine Vision Adaptive image watermarking algorithm based on visual characteristics Gaussian Image Denoising Method Based on the Dual Channel Deep Neural Network with the Skip Connection Design and Realization of Drum Level Control System for 300MW Unit New energy charging pile planning in residential area based on improved genetic algorithm
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1