Research On MAC Protocol For Wireless Sensor Network Based On Data Fusion

As a newly emerging technology integrated by many disciplines,Wireless Sensor Network(WSN)has been widely used in medical monitoring,target tracking,environmental monitoring and military reconnaissance in recent years.In large-scale wireless sensor network applications,a large number of sensor nodes are usually delivered by aircraft randomly to the monitoring area,which leads to massive data in the network.However,the storage capacity and energy of sensor nodes are limited,resulting in massive data not only poses a challenge to the life cycle of the network,but also aggravates wireless channel contention and reduces transmission efficiency.Based on the above,improving mass data transmission and channel usage is crucial for wireless sensor network applications.Data fusion technology is the key technology for saving network energy,reducing data transmission and enhancing the accuracy of data collection.The wireless sensor network MAC layer protocol is the direct control of the wireless channel,and its goal is to rational allocation of wireless communication resources,reduce node collision and improve channel utilization.Therefore,based on the large-scale application of forest fire monitoring and other large-scale applications,this paper studies the data fusion technology and MAC protocol.The main contents are as follows:(1)Aiming at the phenomena of massive data in large-scale monitoring applications,a clustering-based energy-optimized data fusion algorithm CEODA is designed to reduce node energy consumption,reduce data transmission and improve the fusion accuracy.The algorithm is based on the clustering topology,and K-Means algorithm is used to divide the monitoring area.The cluster head is selected by using fuzzy logic considering the energy,the distance of the base station and the number of nearby neighbors.The clustering results are combined with the data correlation.In the stage of data fusion,cluster head node adopts kernel principal component analysis to fuse data,which can reduce the data transmission while ensuring the fusion precision.(2)Aiming at the phenomenon that the converged data in the data fusion technology aggravates the channel competition,DB-MAC based on data fusion and dynamic backoff wireless sensor network is designed to improve the channel utilization of data and reduce the collision Reduce the delay.The data frames in DB-MAC are divided into different types according to whether they are merged or not,and the converged data frames have smaller contention windows than normal data frames.(3)The proposed algorithm is simulated and compared with other algorithms.Simulation results show that CEODA algorithm improves the network life cycle by 701 and 224 respectivelycompared with LEACH and CDSC algorithms in the first node.In each round of energy consumption decreased by 36.9% and 14.3%,CEODA fusion accuracy in both experiments were maintained at more than 98%.In addition,compared with PB-MAC and AS-PW-MAC,DB-MAC decreased by 3.68 times and 27.73 times respectively in terms of average collisions.In terms of data latency,there was a reduction of 0.91 s and 0.20 s,respectively.