张健, 郭星, 李炜. 基于果蝇优化算法的WSN节点定位研究[J]. 微电子学与计算机, 2018, 35(4): 89-92.
引用本文: 张健, 郭星, 李炜. 基于果蝇优化算法的WSN节点定位研究[J]. 微电子学与计算机, 2018, 35(4): 89-92.
ZHANG Jian, GUO Xing, LI Wei. Research of WSN Node Localization Based on Fruit Fly Optimization Algorithm[J]. Microelectronics & Computer, 2018, 35(4): 89-92.
Citation: ZHANG Jian, GUO Xing, LI Wei. Research of WSN Node Localization Based on Fruit Fly Optimization Algorithm[J]. Microelectronics & Computer, 2018, 35(4): 89-92.

基于果蝇优化算法的WSN节点定位研究

Research of WSN Node Localization Based on Fruit Fly Optimization Algorithm

  • 摘要: 针对由测距误差造成的无线传感器网络节点定位精度较低问题, 提出一种基于果蝇优化算法的无线传感器网络节点定位方法.该方法将节点定位问题转化为约束优化问题进行求解, 在求解的过程中利用动态步长机制来控制果蝇种群的寻优范围.当果蝇算法收敛时, 在最优解附近根据测距误差的大小进行震荡寻优, 对寻优产生的果蝇种群进行质心定位得出最终的定位结果.仿真实验表明, 该方法收敛速度快, 定位精度高, 具有较强的抗误差能力.

     

    Abstract: Ranging error results in inaccurate localization of nodes in wireless sensor networks. Focusing on the problem, this paper proposes a WSN node localization method based on the fruit fly optimization algorithm. In this method, the problem of node localization is transformed into a constrained optimization problem, In the process of solving, the dynamic step size mechanism is used to control the optimal range of fruit fly population. When the algorithm converges, in the vicinity of the optimal solution creates new fruit fly populations, Using the centroid algorithm locate the fruit fly population as the final node position.Simulation results show that the method has fast convergence speed, high positioning accuracy and strong error resistance.

     

/

返回文章
返回