Clustering Routing Algorithm In Wireless Sensor Networks

Wireless sensor networks(WSNs)is a wireless communication network which is comprised of a large number of micro-sensors in a self-organizing and multi-hop manner to realize data collection,processing,and transmission in the physical world.At present,it has been extensively used in various fields.Due to the particularity of monitoring area geography location,the sensor nodes cannot be recycled and recharged after being deployed and the small sensor nodes carry less battery energy,resulting in a short network lifetime of the entire WSNs,which limits the sustainability development of WSNs.In order to better realize the existing or potential applications of WSNs,this thesis aimed to improve the network lifetime and reduce the data transmission delay,proposed an improved clustering routing algorithm.This thesis' major research contents as follows:(1)Introducing system structure,main features,key technologies and application prospects of WSNs.The related clustering routing algorithms namely LEACH algorithm,DEBUC algorithm and MRAUC algorithm are examined and analyzed,which is next step research preparation.(2)Aimed at the disadvantages of LEACH algorithm,DEBUC algorithm and MRAUC algorithm,this thesis proposed an improved clustering routing algorithm.Through building the reasonable of clusters and the improved inter-cluster routing to improve the network lifetime and data transmission efficiency.(3)The basic process of this thesis' improved clustering routing algorithm as follows: Firstly,set the threshold T(n)based on the residual energy of the node,the average residual energy of the network alive node,and the distribution density of neighbor node,which improves the cluster head election mechanism to select the appropriate cluster head node.Secondly,optimized the cluster radius R of the cluster head node based on the distance between the cluster head node and base station,the residual energy of the cluster head node and the distribution density of the neighbor node,which generated a reasonable cluster size.Thirdly,an adaptative wireless inter-cluster routing strategy based on improved gradient descent reinforcement learning to calculate the minimum value of weights was applied to data transmission between cluster head and base station,which based on residual energy of the neighbor cluster head node,the distance between the neighbor cluster head node and the base station,and the cluster radius of the neighbor cluster head node.Finally,the thesis' improved clustering routing algorithm compared to LEACH algorithm,DEBUC algorithm and MRACU algorithm through simulation.It can be concluded from the experimental results that this thesis' improved algorithm is more stable in terms of the residual energy variance of nodes,and the fluctuation range was smaller.In terms of network lifetime,compared with the above three algorithms,this thesis' algorithm improved by 1599 rounds,360 rounds and 133 rounds respectively.In terms of data transmission throughput,it was 10.1 times,1.83 times and 1.51 times of the above three algorithms respectively.