Cloud model-based control strategy on cluster communication coverage for wireless sensor networks

For random deployment in sensor networks, there exists uneven node density, seriously reducing the network performance after clustering. The idea of the power control in CDMA is applied to handle the communication coverage control for clusters in wireless sensor networks. The cloud model-based uncertainty reasoning and control mechanism are introduced to adjust the transmit power adaptively to keep the node number within each cluster in an appropriate range in accordance with the node distribution density. The tendentious rules of cloud model ensure the convergence performance of the coverage control, while random process concealled in cloud model ensures the best iteration times in all. After clustering, there exists an appropriate node number within each cluster, improving the network topology. The experiment results validate its rationality and effectiveness.