Research And Implementation Of Wireless Sensor Network Clustering Algorithm Based On The Interest Data Filtering

In the wireless sensor nodes work, the nodes work relying the energy supply, and a topology algorithm can effectively control the energy consumption of nodes and greatly prolong the network lifetime. However, many existing topology algorithms do not synthetically consider the inter node distance, node density, and residual energy of nodes. Moreover, in the data transmission phase the data is not differentiated and sent by nodes.In order to solve the topology control problem, this thesis proposes a topology clustering algorithm based on the node priority and interest data filtering. The algorithm firstly calculate the average distance among nodes, which can compute the inter node distance reflecting the node density. Then, the average distance and the residual energy are transformed into the priority weights for the selection of cluster heads. After that, the cluster heads forward the interest data according to a reasonable classification, and for different kinds of information screening, ultimately reduce the quantity of forwarded data to save energy. Finally, the experimental results show that the proposed algorithm can reduce the energy consumption, compared with several typical algorithms, and thus the algorithm greatly extend the network lifetime.At the end of the article, the ZigBee wireless development kit is used to realize a prototype of cluster head selection. In this prototype, nodes acquire the distance through RF communication for calculating the draw distance, which is combined with its residual energy to get the priority value. Ultimately ordinary nodes will be connected to the corresponding cluster heads, and the data will be transferred through the nodes to the sink.