Sensor deployment optimization based on CVaR submodular utility maximization model

In order to ensure the optimal effect of sensor layout under uncertain conditions, this paper considers the uncertainty of nodes in the initial deployment of nodes, and adopts CVaR submodular utility maximization model to minimize the uncertainty of sensor network layout. In order to quickly and effectively obtain the optimal sensor layout under the model, the traditional greedy algorithm is improved, and the global optimal solution is searched according to the parameter τ existing in the model. At the same time, the lazy evaluation is introduced to decrease time complexity. Simulation experiments show that the CVaR model can effectively improve the robustness of the sensor deployment network when the sensor is laid out under uncertainty. Combined with the improved greedy algorithm, the layout point set can be quickly obtained with high information gain.