With the emergence of computation-intensive mobile applications in wireless networks, the limited computation capacities of some mobile devices (MDs) are not able to satisfy the service requirements and the backhaul of cellular base station (BS) is overloaded. To solve these problems, the combination of mobile edge computation (MEC) technology and device-to-device (D2D) technology is of great concern, which makes MDs have more chances to offload tasks to the network edge, instead of sending them to the remote Clouds, as well as the load of backhaul is reduced effectively. There are several recent studies on combining MEC and D2D technology, but maximizing the number of MDs whose tasks are completed when the tasks are indivisible, and on this basis, reducing the energy consumption of task offloading as far as possible is rarely considered. Aiming to achieve this goal, a computation offloading scheme with D2D for MEC-enabled cellular networks is proposed in this paper, which focus on appropriate task offloading strategies. At first, the optimal problem is transformed to a 0-1 integer programming problem, which can be solved to obtain the maximum number. Then, the energy consumption of task offloading is reduced by exchanging the task offloading strategies between MDs. Finally, numerical simulation results validate that the proposed scheme has relatively better performances than the baseline schemes.
