一种基于UAV的无人海岛监控网络数据收集策略
针对传统的最小跳路由无线传感器网络（WSN ）在数据汇聚上较高的能量开销问题,提出了 一种基于无人机（UAV ）数据收集的动态分簇算法,其主要思想是利用节点剩余能量来确定那些节 点可以当选簇首,同时利用节点坐标位置和设定地分簇半径来划分簇的大小.该算法的优势是能最 大程度地均衡每个传感器节点的能量,使整体的节点剩余的能量维持在同一水平.为了提高数据收 集的效率,采用蚁群算法规划了无人机数据收集的最短路径.仿真结果表明,与相同的分簇算法下 传统的最小跳路由无线传感器网络相比,所提出的基于无人机的无线传感器网络（ UAV-WSN）在能 量利用率和生命周期方面分别提升了 15%和25% ,并且以上两...
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| Published in | 电讯技术 Vol. 58; no. 2; pp. 131 - 137 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
山东科技大学 电子通信与物理学院,山东 青岛266590
2018
崇实大学 电子工程学院,韩国 首尔06978%山东科技大学 电子通信与物理学院,山东 青岛266590 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-893X |
| DOI | 10.3969/j.issn.1001-893x.2018.02.003 |
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| Abstract | 针对传统的最小跳路由无线传感器网络（WSN ）在数据汇聚上较高的能量开销问题,提出了 一种基于无人机（UAV ）数据收集的动态分簇算法,其主要思想是利用节点剩余能量来确定那些节 点可以当选簇首,同时利用节点坐标位置和设定地分簇半径来划分簇的大小.该算法的优势是能最 大程度地均衡每个传感器节点的能量,使整体的节点剩余的能量维持在同一水平.为了提高数据收 集的效率,采用蚁群算法规划了无人机数据收集的最短路径.仿真结果表明,与相同的分簇算法下 传统的最小跳路由无线传感器网络相比,所提出的基于无人机的无线传感器网络（ UAV-WSN）在能 量利用率和生命周期方面分别提升了 15%和25% ,并且以上两种网络的能量利用率高达70%. |
|---|---|
| AbstractList | 针对传统的最小跳路由无线传感器网络（WSN ）在数据汇聚上较高的能量开销问题,提出了 一种基于无人机（UAV ）数据收集的动态分簇算法,其主要思想是利用节点剩余能量来确定那些节 点可以当选簇首,同时利用节点坐标位置和设定地分簇半径来划分簇的大小.该算法的优势是能最 大程度地均衡每个传感器节点的能量,使整体的节点剩余的能量维持在同一水平.为了提高数据收 集的效率,采用蚁群算法规划了无人机数据收集的最短路径.仿真结果表明,与相同的分簇算法下 传统的最小跳路由无线传感器网络相比,所提出的基于无人机的无线传感器网络（ UAV-WSN）在能 量利用率和生命周期方面分别提升了 15%和25% ,并且以上两种网络的能量利用率高达70%. TN915.9; 针对传统的最小跳路由无线传感器网络(WSN)在数据汇聚上较高的能量开销问题,提出了一种基于无人机(UAV)数据收集的动态分簇算法,其主要思想是利用节点剩余能量来确定那些节点可以当选簇首,同时利用节点坐标位置和设定地分簇半径来划分簇的大小.该算法的优势是能最大程度地均衡每个传感器节点的能量,使整体的节点剩余的能量维持在同一水平.为了提高数据收集的效率,采用蚁群算法规划了无人机数据收集的最短路径.仿真结果表明,与相同的分簇算法下传统的最小跳路由无线传感器网络相比,所提出的基于无人机的无线传感器网络(UAV-WSN)在能量利用率和生命周期方面分别提升了15%和25%,并且以上两种网络的能量利用率高达70%. |
| Abstract_FL | Aiming at the problem of high energy overhead in data collection for the traditional minimum hop routing wireless sensor network(WSN),a dynamic clustering algorithm based on unmanned aerial vehicle (UAV) that is employed to collect data is proposed. The main idea is to use the residual energy of nodes to determine which nodes can be elected cluster heads. Simultaneously,the cluster size is divided accord-ing to the node coordinates and the presetting cluster radius. The advantage of the algorithm is that the en-ergy of each sensor node can be balanced to the maximum extent,so that the remaining energy of the whole node is maintained at the same level. In order to improve the efficiency of data collection,ant colony algo-rithm is used to plan the shortest path of UAV. The simulation results show that compared with the tradi-tional shortest multi-hop route WSNs under the same clustering algorithm,the proposed WSN based on UAV(UAV-WSN) is improved by 15% and 25% in energy utilization and lifetime respectively,and the energy utilization of above two WSNs is as high as 70%. |
| Author | 王赛;郝建军;姚亚芬 |
| AuthorAffiliation | 山东科技大学电子通信与物理学院,山东青岛266590;崇实大学电子工程学院,韩国首尔06978 |
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| Author_FL | YAO Yafen HAO Jianjun WANG Sai |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DocumentTitleAlternate | A Data Collection Strategy for Uninhabited Island Monitoring Network Based on Unmanned Aerial Vehicle |
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| Keywords | 无人海岛监控网络 数据收集 uninhabited island monitoring network 动态分簇算法 蚁群算法 unmanned aerial vehicle(UAV) ant colony algorithm wireless sensor network(WSN) 无人机 无线传感器网络 dynamic clustering algorithm |
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| Notes | Aiming at the problem of high energy overhead in data collection for the traditional minimum hop routing wireless sensor network（WSN）,a dynamic clustering algorithm based on unmanned aerial vehicle （UAV） that is employed to collect data is proposed. The main idea is to use the residual energy of nodes to determine which nodes can be elected cluster heads. Simultaneously,the cluster size is divided accord-ing to the node coordinates and the presetting cluster radius. The advantage of the algorithm is that the en-ergy of each sensor node can be balanced to the maximum extent,so that the remaining energy of the whole node is maintained at the same level. In order to improve the efficiency of data collection,ant colony algo-rithm is used to plan the shortest path of UAV. The simulation results show that compared with the tradi-tional shortest multi-hop route WSNs under the same clustering algorithm,the proposed WSN based on UAV（UAV-WSN） is improved by 15% and 2 5 % in energy utilization and lifetime respectively, |
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| Publisher | 山东科技大学 电子通信与物理学院,山东 青岛266590 崇实大学 电子工程学院,韩国 首尔06978%山东科技大学 电子通信与物理学院,山东 青岛266590 |
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| Snippet | 针对传统的最小跳路由无线传感器网络（WSN ）在数据汇聚上较高的能量开销问题,提出了 一种基于无人机（UAV ）数据收集的动态分簇算法,其主要思想是利用节点剩余能量来确定那些节 点可以当选簇首,同时利用节点坐标位置和设定地分簇半径来划分簇的大小.该算法的优势是能最... TN915.9;... |
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| StartPage | 131 |
| SubjectTerms | 动态分簇算法 数据收集 无人机 无人海岛监控网络 无线传感器网络 蚁群算法 |
| Title | 一种基于UAV的无人海岛监控网络数据收集策略 |
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