A new path optimization algorithm based on ant colony——ant colony algorithm has showed great strengths in large scale optimization problem. This paper solved the optimization problem in the area coverage and barrier coverage based on ant colony algorithm. An improved basic ant colony algorithm is proposed. During the process that wireless sensor network try to cover its target area, a lot of redundant nodes are generated, resulting in excessive network energy consumption and incomplete node coverage. Against this problem, an efficient covering algorithm based on point set optimization is proposed. In the algorithm, the Gaussian normal density function and coverage area probability function are utilized during optimization of the point set, so that an optimal point set which meets certain coverage requirements is given through the quantitative relationship between the node sensing radius and number of nodes in the network, and furthermore, the network resource is optimized, the lifetime and Qos of the network are improved, and the network overhead is also reduced. Simulation result shows that: during test results against different coverage area and comparison to PEAS algorithm and GAF algorithm, the effectiveness and stability of the algorithm are verified.