Distributed Data Compression Method for Wireless Sensor Network Based on Apriori Algorithm
Jiyin Zhou · 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture · 2021
The query of sensor storage and perception data is also the query of relationships and time series. This research mainly discusses the distributed data compression method of wireless sensor network based on Apriori algorithm. For the data of each sensor, the Min-Max method is used for standardization, then the segmented aggregation approximation method (PAA) is used for data reduction, and finally the monotonic feature extraction method is used to discretize the time series data. Use Apriori algorithm to mine frequent patterns. The collected data will first be transmitted to the cluster head node. The cluster head node will store the data and process it. The cluster head node optimally determines the common component based on the data of each sensor node, and transmits the measurement result value to the aggregation terminal, and finally at the terminal Jointly restore the signals of each node. The length of the collected data is N=640. Similarly, the error of the reconstruction result of one of the nodes is calculated and then compared. The fastest time is 1.2s. This research helps to reduce the overall energy consumption of the network.