无线通信网络节点定位中的数据融合

Ya Luo, Xiaoyang Liu, Chao Liu
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引用次数: 1

摘要

针对无线传感器网络中存在的定位精度低、能量消耗大、传输延迟等问题,提出了一种无线传感器网络数据融合方法。结合D-S理论,首先构建了无线传感器网络系统模型。然后在分析蚁群算法和最小生成树算法的基础上,提出了一种无线传感器网络数据融合方法。仿真结果表明,无线传感器网络中节点数量越多,其能耗和时延也越大。随着汇聚节点移动速度的增加,平均传输延迟减小,有效数据速率增加。平均能耗也在逐渐增加;所提WSN数据融合方法的性能优于蚁群算法和MST算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Fusion in Wireless Communication Network Node Positioning
Aiming at the problems of low localization accuracy, high energy consumption and delay of transmission in wireless sensor networks, a wireless sensor network data fusion method is proposed. Combined with the theory of D-S argument, the wireless sensor network system model is first constructed. Then based on the analysis of ACO (Ant Colony Optimization) and MST (Minimum Spanning Tree) methods, a wireless sensor network data fusion method is proposed. The simulation results show that the larger the number of nodes in WSN is, the larger the energy consumption and delay are. As the moving speed of Sink node increases, the average transmission delay decreases and the useful data rate increases. The average energy The consumption is also gradually increasing; the performance of proposed WSN data fusion method is better than that of ACO and MST.
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