Research Of Coverage Enhancing Algorithm In Wireless Sensor Network

With the rapid development of the science and Mobile Internet,wireless sensor network(WSN)has been widely used.How to improve the quality of network service and resource utilization is one of the most intrinsic issues in WSN.Among them,coverage rate is an important index of appraising the service quality of network,which can intuitively reflect the desired monitoring ability of network.By using some technologies,the coverage enhancing technology can achieve higher the coverage rate and resource utilization and longer network lifetime with less cost.However,the existing coverage enhancing algorithms have some problems,such as high complexity,unstable performance,and so on.To solve the problems,the dissertation launches some research on two-dimensional coverage problem in directional WSN and three-dimensional coverage problem in all-WSN.The work which has been done includes:(1)Research of coverage enhancing algorithm based on numerical analysis and greedy iteration in directional WSN.The proposed algorithm adjusts the sensor direction by way of greedy iteration,until all sensor directions reach local optimum.Meanwhile,in the process of greedy iteration,greedy iteration is used to simplify the area calculation to reach the reduction of the complexity of the proposed algorithm.The simulation demonstrates that the proposed algorithm is well convergent with high coverage rate and medium execution time.(2)Research of three-dimensional coverage enhancing algorithm based on virtual force in all-directional WSN.When two-dimensional coverage enhancing algorithms are converted into three-dimensional coverage enhancing algorithms,the converted algorithms have some problems.To solve the problems,a three-dimensional coverage enhancing algorithm based on virtual force is proposed.The proposed algorithm uses node repulsion,node attraction and boundary repulsion to ensure the uniform distribution of the sensors.Meanwhile,coverage factor is used to eliminate the unproductive movement.The simulation demonstrates that the proposed algorithm has better convergence and higher coverage rate.