稀疏无线传感网络的移动感知覆盖方法仿真

Simulation of Mobile Sensing Coverage Method for Sparse Wireless Sensor Networks

为解决稀疏无线传感网的区域感知全覆盖问题,利用传感节点的移动,提出了一种稀疏无线传感网络的移动感知覆盖方法(MSC)。在MSC方法中,将整个监测区域划分为多个大小相同的网格,建立权衡丢包率和传输时延的优化模型,提出细菌适应度函数并采用修改的细菌觅食优化算法求解,获得移动传感节点的最优移动路径方案。仿真表明:MSC方法通过移动传感节点的位置、数据存储容量和传输数据时间等信息,能寻找一条全覆盖整个监测区域的最优移动路径,从而降低数据丢包率和数据传输时延。在一定条件下,MSC方法比RAND_D、HILBERT和TCM方法更优。

In order to solve the area-aware full coverage problem of sparse wireless sensor networks,mobile sensor node was used and simulation of mobile sensing coverage method for sparse wireless sensor networks(MSC)was proposed.In the MSC method,the whole monitoring area was divided into multiple grids of the same size.An optimization model which weighs the packet loss rate and transmission delay was established.The modified bacterial fitness function was proposed.Bacterial foraging optimization algorithm was used to solve the model and optimal mobile path solution was obtained.The simulation shows that MSC method algorithm can find an optimal movement path covering the entire monitoring area with the information,such as the location of mobile sensor node,data storage capacity and data transmission time.The MSC method can reduce data packet loss rate and data transmission delay.Under certain conditions,the MSC method is better than RAND_D,HILBERT and TCM method.