The Research Of Intelligent Algorithm Used In The Wireless Sensor Network Coverage Optimization

The composition of wireless sensor network is tiny sensor nodes, these sensor nodes shaping network through organization. The core content of this network research is network coverage control and node deployment, it determines the size of the sensor network awareness and monitoring capability and reflects the quality of service in wireless sensor. In order to achieve the purpose of reducing the coverage blind area of wireless sensor network and improving the ability of sensor nodes to obtain information, It needs a reasonable and effective deployment of network nodes. In recent years, the research of wireless sensor network has been rapidly developed, the research hotspot is through the strategy of coverage control and node deployment to achieve the optimized allocation of network resources. Even in computing power, energy of nodes and communication bandwidth does not meet the conditions, it also can achieve the purpose to improve the quality of monitoring and communication to make the network prolong survival time longer.Intelligent algorithm is a kind of optimization algorithm that does not need centralized control, this algorithm is simple and easy to implement. Swarm intelligence optimization algorithm plays a very important role in the process of production, it improves the production efficiency and saves resource. Due to the complication and constraints of practical engineering, it is very difficult to establish the corresponding mode. So, it is important to search intelligent optimization methods to solve practical problems. It is also a hot research topic.This paper studies the covering control problem based on probability model, raises the cover optimization selection based on artificial fish algorithm, particle swarm optimization and genetic algorithm. The detailed calculation method is given for the coverage performance evaluation. First, turn the optimization goal to objective function of artificial fish algorithm, fitness function of particle swarm optimization and fitness function of genetic algorithm. Then, optimized operation is used to artificial fish algorithm, particle swarm optimization and genetic algorithm based on objective function to make the approximate optimal cover set is quickly calculated. It also can make the coverage of wireless sensor networks improved greatly.This paper researched and discussed wireless sensor network coverage optimization control problems in greenhouses, analyzed the requirements in real-time monitoring and the necessity of network coverage optimization in greenhouses. Using the simulation and considering multiple wireless sensor nodes, utilize artificial fish algorithm for wireless sensor network coverage optimization application in greenhouses and achieved the better average network coverage.