基于蜂窝网络结构的数据融合算法

针对无线传感网中节点能耗同数据精确度之间不均衡的问题，提出一种能够基于蜂窝网络结构的数据融合算法（DFACN）。在基于蜂窝网络的分簇结构中，首先筛选最小能耗的簇头；之后通过数据精确度和节点能耗的计算判断融合因子的大小，动态选取参与融合的簇内节点数；最后簇头完成数据的融合处理。在OPNET仿真环境下，与EECDA和IDDOA算法进行实验对比，DFACN算法的数据精确度分别提高了2.6%和4.7%，节点能耗分别降低了2.7%与3.4%。结果表明，DFACN算法在降低能耗的同时，有效地提高了数据的融合精确度，并且延长了网络的生命周期。

Data fusion algorithm based on cellular network structure

This paper proposed a data fusion algorithm based on cellular network structure(DFACN) to solve the problem of unbalance between node energy consumption and data accuracy in wireless sensor network. In the clustered structure based on a cellular network, first, the algorithm screened the cluster head with the smallest energy consumption. Then it calculated the data accuracy and the energy consumption of the node to the fusion factor in order to select the number of nodes in the cluster dynamically. Finally, the cluster head completed the data fusion automatically. In the OPNET simulation environment, compared to the EECDA and the IDDOA algorithm, the data accuracy of the DFACN algorithm increases 2.6% and 4.7%, the node energy consumption reduces 2.7% and 3.4%. The results show that DFACN algorithm reduces energy consumption while improves the accuracy of data fusion effectively, and extends the life cycle of the network.