The optimization of resource allocation in wireless communication networks can be described as a mixed integer nonlinear programming （MINLP） problem. It is essentially a non-convex NP hard problem. In order to reduce the computational complexity and ensure the optimal performance of the allocation scheme， a binary whale optimization algorithm （WOA） is proposed to allocate wireless resources. Based on the original WOA position update is carried out based on the switch between values 1 and 0. The current position changes are determined by the probability calculated by the humpback spiral movement. Meanwhile， different transfer functions are used to map the continuous search space to discrete actions， and the penalty method and the optimization constraint processing are introduced. Two cases of resource allocation in wireless networks are analyzed in the experiment： The power allocation problem with maximum confidentiality and the mobile edge computing migration. The results show that the proposed method has excellent system performance and obtains similar effects to other methods， but its convergence speed is faster and its complexity is lower.