Study On Optimization Of Control Algorithm For Wireless Sensor Networks Deployment

It is witnessed that the Wireless Sensor Networks have been deployed in a wide range of applications including earthquake, medical monitoring, environmental monitoring, weather forecasting, military reconnaissance, to just name a few. WNSs have frequently changing topology structure, limited node energy, and its usually applied in some extreme environments, so how to deploy network nodes and how to improve the efficiency of the deployment of wireless sensor networks becomes an important consideration. The goal of research is to obtain a comprehensive and accurate monitoring results, save the energy and prolong the life of the network.Currently, the best deployment of node in Wireless Sensor Networks is still exploring. The immature control algorithms drive the researcher to seek an efficient optimization algorithm to solve this problem by the analysis and improvement of common control algorithm. This paper deals with the WSNs deployment in SPSO algorithm at first. And based on the algorithm, a new PSO algorithm——HS-PSO algorithm is proposed to improve the efficiency of WSNs deployment.The main contribution of this paper regarding to the optimization of node coverage problem for WSNs are summarized in the following aspects:① Through in-depth study of structural features in WSNs, the mode of operation of WSNs deployment problem is fully understood. After analyzing common control algorithms of the nodes coverage and performance indicators of covering efficiency in WSNs, this paper constructs the simulation model of WSNs deployment and proposes the fitness function of the control algorithms.② This paper analyze the basic principle of PSO algorithm and illustrate the principle and operation process of SPSO algorithm and HS algorithm, which provides a firm foundation for improving the existing algorithms and conducting the simulation experiments.③ Because of the better global convergence characteristics of HS algorithm, this paper proposed an improved PSO algorithm(HS-PSO) which based on HS algorithm and by a profound study of the SPSO algorithm principle. The basic PSO algorithm suffer from the problem of falling into local optimum easily. This problem is well addressed by the novel HS-PSO algorithm.To prove the effectiveness of the improved algorithm, this paper use the Goldstein-Price functions and Griewank functions to do the simulation experiments with the three kinds of algorithms above. These experiments demonstrate the global convergence of HS-PSO algorithm is the best among all algorithms.④ This paper uses the SPSO algorithm and HS-PSO algorithm do the simulation experiments in the same network coverage model. To determine the simulation experiments have the better effect of coverage, this paper uses comparative analysis of a lot of simulation experiments results with a variety of parameters values. By comparing and analyzing the two kinds of optimization algorithms with the PSO algorithm in simulation results, it is obvious that the performance of SPSO algorithm outperforms the PSO algorithm, and the HS-PSO algorithm outperforms SPSO algorithm in WSNs deployment.