| 摘要: |
| 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%。 |
| 关键词: 无线传感器网络；无人机 动态分簇算法；无人海岛监控网络；数据收集；蚁群算法 |
| DOI： |
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| 基金项目:国家自然科学基金资助项目（61471224）；山东省自然科学基金项目（ZR2014JL044） |
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| A data collection strategy for uninhabited island monitoring network based on unmanned aerial vehicle |
| WANG Sai,HAO Jianjun,YAO Yafen |
| () |
| Abstract: |
| 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 according to the node coordinates and the presetting cluster radius. The advantage of the algorithm is that the energy 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 algorithm is used to plan the shortest path of UAV. The simulation results show that compared with the traditional shortest multi-hop route WSNs under the same clustering algorithm,the proposed WSN based on UAV(UAV-WSN) is improved by 15〖WT《Times New Roman》〗%〖WTBZ〗 and 25% in energy utilization and lifetime respectively,and the energy utilization of above two WSNs is as high as 70%. |
| Key words: wireless sensor network(WSN) unmanned aerial vehicle(UAV) dynamic clustering algorithm uninhabited island monitoring network ant colony algorithm |
