Wireless Multimedia Sensor Network Coverage Optimization Based On ACO And PSO Algorithm

Wireless multimedia sensor networks have the advantages of rich sensing information and high quality of network service. At the same time there are many new problems to be studied. Among these,the ability of network coverage reflects the ability of WMSN to obtain external information and it is the basis for other studies directly affect the service quality of the network. As a basic problem of sensor networks, coverage optimization is an important evaluation index of network performance. Effective coverage control strategy can improve the coverage of WMSN network and improve the quality of network coverage.In the premise of ensuring the quality of service WMSN use the directional sensor nodes for extend the network life cycle and adjust the direction, location of the node in the network coverage requirements. There will be to the sensor node by sow the way of randomly deployed in the target area, appeared more network coverage areas overlap and coverage holes. A coverage optimization algorithm for WMSN based on ant colony optimization and particle swarm optimization is proposed in this thesis to solve this problem.Ant colony optimization algorithm showing advantages in solving complex combinatorial optimization problem with positive feedback, parallelism, robustness. However, the algorithm needs long time slow convergence and easy to fall into local optimum. PSO has better global search ability which can efficient parallel computing is to deal with continuous optimization and search problems, but the algorithm local search optimization ability is weak, it is easy to fall into premature convergence.ACO-PSO is applied to the optimization of WMSN coverage. First with the ACO algorithm local search and searching for the optimal path in the local area, the individual and the optimal solution of the particle are updated. Then using PSO to global search and the global optimal solution is obtained by comparison. According the concentration of pheromone to adjust the coverage network position sensor and sensing direction to achieve wireless multimedia sensor network coverage optimization after comparing the global optimal solution. In the WMSN area coverage simulation experiment comparison of ACO-PSO with a single ant colony algorithm, particle swarm optimization algorithm to solve the coverage optimization. Experimental results show that the proposed algorithm is more superior than the single algorithm, and can effectively improve the coverage rate of WMSN...