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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.
Reducing power consumption and prolonging the life span are an important issue in wireless sensor networks, and at the same time, it is possible to capture the change of state of the target in time while maintaining a certain coverage quality in the monitoring area.A widely used strategy is to select a system that meets the quality requirements of the monitoring area The minimum node set as a working node and other redundant nodes are closed.Therefore, controlling node dormancy and maintaining the quality of coverage in sensor networks are two important aspects.A mathematical model is proposed to solve the problem that satisfies the minimum required for any given coverage quality Nodes.Experiments show that when the ratio of the sensing area to the sensing area is large, the proposed method can calculate the minimum required number of working nodes more accurately and the complexity of the method is low. The sensing area of the sensor nodes can be any shape It is an NP hard problem to maximize the network coverage quality and node dormancy rate at the same time. Genetic algorithm is used to simulate the experiment to solve this problem tentatively, which brings great significance for the practical application of the sensor network.