| With the rapid development of science and technology in today’s world,people are more and more enjoying the convenience brought by science and technology,and they have begun to vigorously develop the Internet of Things technology.As an important branch of the Internet of Things,wireless sensor networks are also highly valued by researchers.Wireless sensor network is an intelligent network composed of several sensor nodes,which mainly have functions of data collection,data processing and data transmission.Since the coverage and energy consumption of nodes are the key indicators to measure the network performance,this paper studies them from these two aspects.(1)In view of the defects of low convergence speed and low global detection ability of CS algorithm,this paper optimizes it from two aspects: step size and optimal solution.Firstly,the momentum gradient descent method and the root mean square method are used to optimize the step size to improve the convergence speed of the algorithm,and then the Cauchy Gaussian variation factor is used to improve the global detection ability of the algorithm,so that it can better find the global optimal solution.Simulation experiments show that the coverage optimization algorithm can improve the coverage rate of sensor nodes better;(2)In view of the uneven distribution of cluster head nodes in the EEUC algorithm and the constant competition radius,which leads to the unbalanced energy consumption of nodes,this paper proposes the idea of network partitioning,and selects the cluster head nodes from the remaining energy of the node and the spatial position.,to make the distribution more uniform,and then based on these two factors,the calculation formula of the competition radius is optimized,so that it can make reasonable changes with the operation of the network and balance the energy consumption of nodes.Simulation experiments show that the routing optimization algorithm can effectively prolong the life cycle of the network. |
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