Mobile Node Deployment based on Improved Probability Model and Dynamic Particle Swarm Algorithm

In order to realize node deployment in monitoring area and improve the network coverage, this paper propose a mobile node deployment method based on improved probability sensor model and dynamic multiple population particle swarm algorithm. Firstly, the improved probability sensor model was introduced by adding the energy factor to the traditional probability model, and then the node deployment mathematical model was given based on the improved probability sensor model considering the network coverage rate and energy factor. Then the SOM algorithm was used to divide the particle population to several sub populations, and the dynamic multiple population PSO method was designed to get the optimal node deployment solution in every sub-population. The simulation experiment shows the method in this paper can deploy mobile nodes evenly in monitoring area, the network coverage and energy were considered, and compared with the other methods about node deployment, it has higher coverage rate and longer network life cycle. Therefore, the proposed method is likely to have more priority and application value.

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