基于感知概率的无线传感器网络k重覆盖算法*

基于布尔感知的无线传感器网络多重覆盖控制模型未考虑实际应用中环境因素对节点感知能力的影响，为弥补这种不足，提出了一种分布式k重覆盖算法（KCAPSM），该算法采用了感知概率模型，依据节点感知能力的强弱，将监测区域中的任一点被相关节点监测的情况赋值为某一概率，并通过节点与邻居交换信息，根据能量大小竞选找出k组不相交工作节点集，保证监测区域中每一点被k重覆盖。实验表明，KCAPSM算法让冗余节点处于休眠状态，节省了网络能量，优化了资源。

k-coverage algorithm based on probabilistic sensing model in WSN

Binary-detection model based method for k-coverage controlling in wireless sensor network is not practicable without consideration of the environment factors. This paper proposed a k-coverage distributed algorithm based on probabilistic sensing model (KCAPSM). Gave any point in the target area sensed by a sensor value based on the sensing capability, and in KCAPSM a sensor compared its residual energy with the neighborhood. They cooperated to construct k working covers that provided probabilistic k-coverage for the whole target region. Experimental results display that KCAPSM made the redundant nodes sleeping, save the energy of the network, and optimize the resources.