With the flourishing of smart mobile devices (e.g., smartphones, tablets), development of mobile cloud computing has received more and more attentions from both industry and academia. Compared with the traditional way of executing large- scale computational tasks on powerful desktop computers and the cloud, mobile cloud computing is featured by the ubiquitous availability, flexibility, and low-cost. However, this feature also brings challenges when we build the satisfactory mobile computing system. First, the computational power on a mobile device is not comparable with that on a personal computer such that many computation-intensive tasks cannot be independently handled by mobile devices. Second, offloading computational tasks to the cloud introduces additional monetary costs (e.g. wireless communication cost, computational service cost), which may be pricy for users. In this paper, we propose a novel connectivity- aware task scheduling paradigm to enable mobile device users to accomplish computation-intensive tasks cooperatively in the device-to-device (D2D) network by incorporating the "fog" - aggregate of computational powers in the ad-hoc. A supernode at the base station is responsible for scheduling cooperation tasks based on user mobility. To further enhance the quality of experience (QoE) for the users, we propose a lightweight heuristic algorithm to perform task scheduling to ensure low cooperative task execution time. Simulation results show that our cooperative paradigm efficiently reduces the average task execution time for mobile device users in the D2D network.