Optical networks have been widely used due to their advantages such as large capacity, high transmission rate, transparent business, and low loss. With the increase of user scale and transmission needs, the frequency of insufficient traffic in optical networks has increased, which has constrained the development of optical networks. Therefore, a cross source scheduling method for optical network traffic big data based on clustering is proposed. Firstly, cluster clustering algorithm is used to process big data of optical network traffic. Secondly, the XGBoost model is used to predict the next moment of optical network traffic. Build a mathematical model for cross source traffic scheduling with the goal of minimizing costs, and determine the constraints of the constructed model. Finally, using genetic algorithm as a tool, obtain the optimal solution for cross source scheduling of traffic, and execute the optimal solution to achieve cross source scheduling of optical network traffic big data. The experimental results show that the clustering results of optical network traffic big data obtained by the proposed method are consistent with the expected clustering results of optical network traffic big data. The minimum cost of cross source traffic scheduling is 160 000 yuan, indicating that the proposed method has better performance in cross source traffic scheduling.