Research On Fuzzy Logic Clustering And Data Fusion In Wireless Sensor Networks

Wireless Sensor Network(Wireless Sensor Network,WSN)consists of a large number of wireless nodes that are distributed in a specific area,with the ability to perceive,store and communicate.WSN has a wide range of applications.Such as applied to the forest fire prevention,wisdom blocks,intelligent wear,train station safety monitoring.Due to the limited characteristics of the wireless sensor network,it is necessary to fuse the collected datum to save the consumption of energy and improve the accuracy of the data.Therefore,wireless sensor network data fusion technology has become one of the research priorities.This paper will regard saving energy consumption as the basic requirement,and consider improving the accuracy and real-time of data fusion as the main goal.This paper does an innovative research on technology of clustering and data fusion.The details of this paper are as follows:Firstly,this paper introduces the background of the wireless sensor network,the architecture,the network characteristics,and the key technology of the wireless sensor network which is data fusion technology,and analyzes the classification,performance and limitations of the data fusion algorithm.Secondly,this paper proposes a new energy enhanced unequal fuzzy clustering algorithm(EEUFC)by analyzing the existing clustering technology.The algorithm calculates the relative density of the nodes and the distance to the base station,and then introduces the fuzzy theory to estimate the competition radius,and regards the relative density in the competition radius and the residual energy as the reference variable of the final cluster head.When complete clustering,the nodes select the cluster head according to the distance and the cost.It is better to avoid hot spot,and it balances the energy consumption.Thirdly,this paper applies fuzzy logic and matrix weighting to data fusion technology.Considering the requirement of accuracy and real-time in data collection and transmission,a fuzzy weighted algorithm for data fusion is proposed(FWADF).The algorithm is based on the clustering model,taking into account the impact of external factors on the accuracy of the data,through the calculation of credibility,cluster head and base station will fuse datum respectively to ensure that provide accurate and real-time data information to users.Finally,the performance of the proposed algorithm is verified by using the simulation software Network Simulator-Version 2(NS-2).The experimental results show that the energy enhanced unequal fuzzy clustering algorithm balances the energy of nodes,and the fuzzy weighted algorithm for data fusion improves the data accuracy.They both extend the life cycle of the network.