Research On Data Aggregation Algorithm Based On Time Correlation In Cluster Sensor Network

In today's rapid development of wireless sensor networks(WSNs),each common node is used to collect the data of the external environment,and transmit the data information it continuously perceives to the aggregation node.Then the aggregation node forwards the data layer by layer to the base station through the sink node,and the base station carries out a series of analysis,processing and decision-making on the collected data.And the final result is transmitted to the terminal application system or users through the remote Internet or satellite.Nowadays,because of WSNs' s advantages of flexibility,practicality and low cost,it has been applied in many fields such as military,agriculture,industry,medical health and so on.At the same time,the disadvantages of sensor nodes in computing,storage,energy consumption and security also restrict the development of wireless sensor network.Therefore,how to reduce the amount of data transmission and the energy consumption of nodes on the basis of ensuring the data accuracy is an urgent problem to be solved in wireless sensor networks.In WSNs,data aggregation technology is used to aggregate the physical data of the target environment collected by nodes,which can effectively remove the redundant data in the network,reduce the amount of data transmission,improve the accuracy of fusion results,and the utilization of scarce resources in wireless sensor networks.This paper studies a large number of aggregation algorithms proposed,makes reasonable improvements,and proposes two aggregation algorithms.:(1)In order to improve the efficiency and accuracy of wireless sensor network,according to the characteristics of time correlation of data collected by nodes,a data aggregation algorithm ESDP based on exponential smoothing prediction model is proposed.The algorithm uses the optimized exponential smoothing method to build the prediction model,and gives different weights to the data collected by each node in different periods to predict the data,and uses the difference transmission method to reduce the size of the data packet.Finally,the cluster head of data is aggregated.The simulation results show that the algorithm can balance the accuracy of data aggregation and the energy consumption.(2)In order to solve the problem of low reliability of data in wireless sensor network,a data aggregation algorithm TGDA based on trust and gray model is proposed.In the process of data aggregation,the algorithm introduces the mechanism of data prediction and trust,that is,cluster head will detect abnormal nodes before data aggregation,filter out abnormal nodes,and use gray model to predict the missing data of abnormal nodes.The simulation results show that TGDA algorithm can reduce the traffic of the network further,and make the result after aggregation more reliable and closer to the actual situation.