The collaboration network of mobile edge computing (MEC) and device-to-device (D2D) technology takes into consideration multiple devices, where the final output of multiple wireless devices is used as the input of a subtask on another device. The optimal resource allocation (offloading transmit power and local CPU frequency) and task offloading decisions are studied to minimize the weighted sum of the energy consumption of wireless devices and the task completion time. First, given an offloading decision, the closed expression of offloading transmit power and local CPU frequency are derived, and the convex optimization method is used to find the solution to the problem. Then, on the basis of the one-climb policy, a low-complexity linear search algorithm is proposed, which can obtain the best offloading decision in linear time. Numerical results show that the performance of this strategy is significantly better than that of other representative benchmark tests.