Research On Cluster-based Routing Algorithm And Data Fusion Technology In Wireless Sensor Networks

The wireless sensor network is a self-organized network through wireless communication which is composed of multiple sensor nodes.These nodes are deployed in the monitoring area and transmit the regional data information to users through cooperative perception,which becomes the link between humans and nature.However,the energy resources of sensor nodes are limited and difficult to be supplemented.And the network is vulnerable to external environment interference.This thesis mainly studies how to extend the network lifetime and ensure the reliability of the data through clustering and data fusion technology under the premise of limited energy of nodes.The main research contents are as follows:1.Clustering is an effective method for reducing energy consumption in wireless sensor networks.In a multihop clustered network scenario,each sensor node transmits data to its own cluster head,and the cluster head aggregates the data from its member nodes and forwards it to the base station via other cluster heads.However,the “hot spot” problem is prone to occur in clustered wireless sensor networks because cluster heads closer to the base station have heavier intercluster forwarding tasks.To address this problem and reduce network energy consumption,this thesis proposes an unequal clustering algorithm based on interval type-2 TSK fuzzy logic theory in the networking phase.The relative distance to the base station,residual energy,and node density are considered as the inputs of an interval type-2 fuzzy logic system.Through fuzzy reasoning,outputs are acquired that can be used to optimize the cluster heads and determine the cluster sizes.Simulation results verify that the unequal clustering algorithm proposed in this thesis can effectively balance energy consumption and enhance energy efficiency because it has better performance in network lifetime and network throughput than other comparison clustering algorithms.2.To improve the energy efficiency and data reliability of wireless sensor networks,an energy efficient data fusion algorithm based on clustered wireless sensor networks is proposed in the data collection and transmission phase.This algorithm runs in the clustered network,in which the process of data collection and transmission is divided into several periods.Sensors collect data in time slots of the period and form a data vector whose dimension will be reduced to reduce the transmission load.At the same time,the interval type-2 fuzzy system is used to generate data reliability factors considering environmental interference to ensure the reliability of data.Each cluster head receives and distributed processing the data from their member nodes.After removing redundant data by the similarity function,the fused data is sent to the next hop cluster head or base station.Simulation results verify that the data fusion algorithm proposed in this thesis has lower bandwidth occupancy,lower energy consumption,and higher data accuracy than PFF,REDA,and SCDRE.