Study On Optimization Technology Of Internet Of Things Based On Topology Control

With the progress of technology and economic development,the Internet of things has become a hot topic and has become an indispensable part of life.Because it is powerful function and intelligence.As we know,things can automatically obtain the information around,which makes the network node plays an important role.Network node are generally composed of a large-scale topology.In order to get a long time of the network,it requires the network topology should be more reasonable,the energy is to be applied more reasonable.It is one of the important research target to a better performance and lower energy consumption of network topology.This paper mainly analyzes and studies the network topology of the Internet of things.The existing algorithm and genetic algorithm are proposed for LEACH topology optimization method(LEACH-GA).In the cluster head stage of LEACH-GA algorithm,we should think about basing on threshold modification of residual energy of the cluster head selection factors.It is considered of cluster first,the node number of neighbor nodes and node.The node is elected the first cluster.The cluster head will be selected more reasonable in the establishment stage of the cluster.Using genetic algorithm fitness function calculation determines the value of a more reasonable clustering structure by MATLAB.Simulation shows that the improved algorithm can improve the life cycle of the node and the data amount.The algorithm improved network structure more reasonable.This paper apply for a design.The design of hardware circuit diagram to realize LEACH-GA algorithm,to realize the algorithm by using the FPGA chip.This paper combinated network nodes with the proposed algorithm.The experimental result show that the LEACH-GA algorithm can improve the energy utilization ratio of the network topology in the Internet of things to prolong the network life time.