The invention belongs to the technical field of communication data distributed optimization, and discloses a double-event-driven distributed optimization method based on discrete iteration, which is based on a double-event-driven communication mechanism, and transmission information received by a network node is only information of an auxiliary variable at the driving moment of a neighbor node ofthe network node. The method comprises the steps of calculating an optimization state in combination with the information of the own driving moment until the auxiliary variable converges to obtain a convergence value of the optimization state; and substituting an original optimization function to obtain an optimal value. According to the method, the convex optimization problem under the equality constraint condition can be solved under the strong connectivity balance directed communication network, and system initialization can be avoided; and a double-event-driven communication strategy is sampled, so that the waste of communication resources is avoided to the greatest extent, and the communication cost is saved. Meanwhile, the method is based on a discrete iteration mechanism, and the Zeno phenomenon is naturally avoided. According to the method, a theoretical basis is laid for distributed optimization application under the directed communication network, and the application range ofthe method is expanded.