Study Of Temporal-spatial Correlation Based Data Fusion Algorithm In Wireless Sensor Networks

As the underlying technology of Internet Of Things (IOT), Wireless SensorNetwork (WSN) collects and transmits all kinds of information in the monitoring area,providing real time and reliable data for military defense, remote medical treatment andenvironmental monitoring applications. It is the key technology of informationtransmission of IOT. However, WSN nodes are distributed densely and samplefrequently. The temporal-spatial correlation between sensed data causes redundanttransmission. Huge amounts of redundant data transmission bring huge pressure to therestricted energy, storage capacity and network bandwidth of WSN. Data aggregationcan effiecently reduces the redundant transmission data, improve the efficiency andaccuracy of collection data. Therefore, the study on WSN data aggregation has a veryimportant academic significance and engineering value.This paper deeply studies the principle, characteristics and performance index oftypical data aggregation algorithm. According to the temporal correlation of sensed dataof the single WSN node and the spatial correlation of sensed data of the multiple WSNnodes, a architecture of temporal-spatial correlation based data aggregation algorithm isproposed and two effective data aggregation algorithms are presented.The main research contents in this paper are as followes:According to the issue that the sensed data of single WSN node has high redundancy, adata aggregation is proposed based on temporal correlation. On the basis of the segmentone-dimensional linear regression model, it establishes prediction model via analyzingtemporal series of sensed data in WSN. According to the various parameters of themodel and the given errors, it adaptively adjusts the next acquisition time anddynamically optimizes regression model. Simulation and experiment show that thisalgorithm can reduce the amount of collection data and transmission data under thecondition of different data changing rate, meeting the data accuracy.According to the issue that the sensed data of the multiple WSN nodes has highredundancy, a data aggregation is proposed based on spatial correlation. According tothe degree of WSN sensed data spatial correlation, the monitoring area is divided intoseveral correlated region. Each correlated region selects a representative node.According to residual energy of representative node’s and the distance to the sink node,a cluster head is selected. The representative node aggregates the correlated region’s sensed data and transimits it to the cluster head. The cluster head forwards the data tothe sink. Simulation and experiment show that this algorithm makes the representativenodes and the cluster heads uniform distribution, small amount of data transmission andhigh precision of sensed data. The algorithm has good performance of energy efficiency.