基于精英遗传算法的无线传感器网络能量优化路由

Jaya Mishra, Jaspal Bagga, Siddhartha Choubey, I. Gupta
{"title":"基于精英遗传算法的无线传感器网络能量优化路由","authors":"Jaya Mishra, Jaspal Bagga, Siddhartha Choubey, I. Gupta","doi":"10.1109/ICCCNT.2017.8204110","DOIUrl":null,"url":null,"abstract":"A key challenge in wireless sensor network (WSN) is represented by energy constrained on sensor nodes i.e. sensor nodes have limited available energy. Thus energy must be used in optimized manner during the network operation. Most of routing algorithm use minimum hop distance and minimum transmission energy model. In such case same path is used many times which leads to drainage to energy of sensor nodes falling in routing path. Some time energy of nodes exhausted result in network partition. In this paper effort has made to develop energy optimized routing algorithm for WSN using genetic algorithm and further we tried to develop elitist genetic algorithm for routing. Simulation results show that elitist genetic algorithm based routing extend network lifetime 4% to 11% compared to genetic algorithm approach and 10% to 19% traditional shortest path approach. Elitist GA raised packet delivery ratio 3% to 8% and 5% to 13% compared to genetic algorithm approach and compared to traditional shortest path approach respectively for WSN routing.","PeriodicalId":6581,"journal":{"name":"2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT)","volume":"48 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Energy optimized routing for wireless sensor network using elitist genetic algorithm\",\"authors\":\"Jaya Mishra, Jaspal Bagga, Siddhartha Choubey, I. Gupta\",\"doi\":\"10.1109/ICCCNT.2017.8204110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A key challenge in wireless sensor network (WSN) is represented by energy constrained on sensor nodes i.e. sensor nodes have limited available energy. Thus energy must be used in optimized manner during the network operation. Most of routing algorithm use minimum hop distance and minimum transmission energy model. In such case same path is used many times which leads to drainage to energy of sensor nodes falling in routing path. Some time energy of nodes exhausted result in network partition. In this paper effort has made to develop energy optimized routing algorithm for WSN using genetic algorithm and further we tried to develop elitist genetic algorithm for routing. Simulation results show that elitist genetic algorithm based routing extend network lifetime 4% to 11% compared to genetic algorithm approach and 10% to 19% traditional shortest path approach. Elitist GA raised packet delivery ratio 3% to 8% and 5% to 13% compared to genetic algorithm approach and compared to traditional shortest path approach respectively for WSN routing.\",\"PeriodicalId\":6581,\"journal\":{\"name\":\"2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT)\",\"volume\":\"48 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCNT.2017.8204110\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCNT.2017.8204110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

无线传感器网络(WSN)的一个关键挑战是传感器节点的能量约束,即传感器节点的可用能量有限。因此,在电网运行过程中,必须优化利用能源。大多数路由算法采用最小跳距和最小传输能量模型。在这种情况下,同一路径被多次使用,导致传感器节点在路由路径上的能量消耗。当节点能量耗尽时,会导致网络分区。本文利用遗传算法开发了无线传感器网络的能量优化路由算法,并在此基础上尝试开发最优的遗传路由算法。仿真结果表明,与遗传算法相比,基于精英遗传算法的路由使网络寿命延长4% ~ 11%,比传统最短路径方法延长10% ~ 19%。对于WSN路由,与遗传算法和传统最短路径方法相比,精英遗传算法分别将分组传输率提高了3% ~ 8%和5% ~ 13%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy optimized routing for wireless sensor network using elitist genetic algorithm
A key challenge in wireless sensor network (WSN) is represented by energy constrained on sensor nodes i.e. sensor nodes have limited available energy. Thus energy must be used in optimized manner during the network operation. Most of routing algorithm use minimum hop distance and minimum transmission energy model. In such case same path is used many times which leads to drainage to energy of sensor nodes falling in routing path. Some time energy of nodes exhausted result in network partition. In this paper effort has made to develop energy optimized routing algorithm for WSN using genetic algorithm and further we tried to develop elitist genetic algorithm for routing. Simulation results show that elitist genetic algorithm based routing extend network lifetime 4% to 11% compared to genetic algorithm approach and 10% to 19% traditional shortest path approach. Elitist GA raised packet delivery ratio 3% to 8% and 5% to 13% compared to genetic algorithm approach and compared to traditional shortest path approach respectively for WSN routing.
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