FCM-AFSA的无线传感器网络多目标跟踪节点任务分配方法

多目标跟踪是无线传感器网络重要应用之一。提出了基于离散人工鱼群算法的无线传感器网络多目标跟踪节点任务分配方法。该方法首先利用类间距阈值的模糊C均值聚类算法，估计监测区域可能出现的目标数量和目标位置；再根据任务分配的目标函数，使用改进的离散人工鱼群算法优化目标函数，从而得到任务分配方案，并同其他算法进行比较。仿真实验结果表明，该方法比最近邻方法、MEM方法以及粒子群算法的能耗有所降低，任务分配时间比最近邻方法、MEM方法以及粒子群算法有所减少。因此，所提出的改进算法能有效地提高无线传感器网络的综合性能，满足实际应用的需求。

FCM-DAFSA based multi-target tracking node taskallocation method for wireless sensor network

Multi target tracking is one of the important applications of wireless sensor networks. A DAFSA (Discrete Artificial Fish Swarm Algorithm) based multi target tracking node task allocation method for wireless sensor network is proposed. Firstly, the class distance threshold fuzzy C means clustering algorithm is used to estimate the number of potential targets and their locations in the monitoring region. Secondly, according to the objective function of task allocation, an improved DAFSA is used to optimize the objective function so as to get the task distribution and is compared with other algorithms. Simulation results show that the proposed algorithm has lower energy consumption and less task allocation time than the nearest neighbor method, MEM method, and particle swarm optimization algorithm. Therefore, it is concluded that the proposed algorithm can effectively improve the overall performance of the wireless sensor networks and meet the needs of practical application.