<p>Due to the rapid growth of terminal devices in wireless cellular networks, the backhaul network congestion problem is very serious. Effective content storage strategies can reduce backhaul network congestion and improve the quality of service provided to mobile users. However, the content storage strategy largely depends on the proper resource allocation. Fortunately, computation offloading can optimize the utilization of resources such as spectrum, improve processing efficiency, and extend the battery life of terminal devices. In this paper, it is worthwhile to discuss the joint optimization problem of resource allocation, data content storage strategy and computation offloading decision in wireless cellular networks with mobile edge computing (MEC). Since traditional resource allocation schemes do not combine computation offloading and storage, the joint optimization problem of resource allocation, data content storage strategy and computation offloading decision in wireless cellular networks with MEC is formulated as a utility maximization problem in order to maximize the system utility in this paper. Due to the existence of binary variables and variable product terms in the original problem, the optimization problem is a nonconvex optimization problem, which is difficult to solve. In this paper, the original nonconvex problem is considered as a convex problem according to the techniques of product term substitution and variable relaxation, and its convexity is proved. Aiming at the high complexity and signaling cost of the centralized algorithm, the optimization problem is divided into sub-problems and a novel distributed resource allocation algorithm (DRAA) is proposed to solve this problem. In DRAA, local variables, global variables and Lagrange multipliers are updated until the stop standard thresholds meet the condition. The simulation results show that, compared with other schemes, the proposed scheme can obtain higher system revenue, faster convergence and lower computational complexity.</p>