降低功耗、延长寿命是无线传感器网络的一个重要问题,同时,对监测区域保持一定的覆盖质量才能及时捕捉到目标的状态变化.一种广泛采用的策略是选出能够满足监测区域质量要求的最小节点集作为工作节点,关闭其他冗余节点.因此,传感器网络中控制节点休眠与保持覆盖质量是两个重要方面.提出了一个数学模型,求解满足任意给定覆盖服务质量下所需的最小节点数.实验表明,当监测区域与节点感知区域比值较大时,提出的方法更为准确地计算出所需最小工作节点数,且此方法复杂度低、传感器节点的感知区域可以为任意形状.网络覆盖质量与节点休眠率同时达到最大化是一个NP难问题,采用遗传算法进行仿真实验尝试性解决这一问题,为传感器网络实际应用带来重要意义.
Extending lifetime by scheduling node state and maintaining the coverage quality are two important aspects in wireless sensor networks (WSNs). It was presented a mathematical model to compute minimum number of nodes under any given required coverage quality. Simulation results demonstrate that our approach is more accurate to compute minimum number of working nodes when the ratio of target region to sensor region is larger, and the complexity of this method is lower while the sensor's region can be perceived as arbitrary shapes. It is an NP-hard problem that network's coverage quality and ratio of sleeping nodes get to maximize together. It tried to solve this problem by using genetic algorithm for the experiments, which is significant in WSNs for the practical applications.