摘要:
本文分析了现有的路由及数据融合算法的优势与缺陷，提出了采用n阶移动平均的数据融合算法，充分利用节点间的数据黏性，使算法不仅可以跟踪环境变化，而且能够迅速捕捉到不符合趋势的环境变动。算法借鉴了半静态聚簇路由机制在节点管理机制的优点，使得WSN可以以较高的效率队簇内节点进行管理，使能耗更加均衡。最后设计了多个模拟场景的实验方案，将本文提出的算法进行各方面的可行性分析，阐释了本文方案在过滤冗余信息、延长网络寿命上的有效性。
Abstract: In this paper, the advantages and detects of routing and data fusion algorithm are analyzed, and a new method based on n-average value of split is proposed. By using data viscosity, this algorithm could not only sense the changing of environment, but also find the abnormal change. Using the advantages of semi-static clustering in managing sensor nodes, the efficiency of routing is obviously improved, and the energy consumption is more balanced. At last, a series of experiments are designed to prove the performance of this algorithm, and based on the experiment results, the ef-ficiency in data filtering and prolonging networks’ lifetime is analyzed.