In cloud radio access network (C-RAN), computation-intensive tasks can be offloaded from mobile devices (MDs) to the powerful computing node in C-RAN, i.e., baseband unit (BBU) pool, through cooperation radio at remote radio heads (RRHs), for effective task processing and improved user experience. In the existing works, computational resources in the BBU pool are always allocated to MDs exclusively, resulting in poor resource utilization and deteriorative task processing delay. Alternatively, we adopt a sequential computation model to enhance computing performance, which is proved through theoretical analyses in this paper. In this model, a task scheduling issue should be addressed in the BBU pool to determine the optimal processing order for tasks. Then, one task's completion time is jointly determined by its scheduling order and arrival time in the BBU pool. Hence, to minimize the maximum task completion time, we jointly optimize cooperative radio at RRHs and task scheduling in the BBU pool. By leveraging the specific property of formulated problem, we propose an effective computation offloading algorithm to achieve a local optimal solution in block coordinate descent manner. Finally, simulation results present the convergence and advantage of our proposed algorithm.