Summary form only given. Among the schemes providing efficient CPU allocation for coexisting multimedia applications and nonreal time tasks, proportional share scheduling is widely used for its flexibility and fairness. However, this method faces the challenge of setting reasonable shares for a set of tasks with dynamically changing resource requirements. Existing solutions for this problem either ignore the needs of important tasks or are complex to realize. This paper proposes an IMAC, an importance-level based adaptive CPU scheduling scheme, to solve the problems. It adjusts the CPU allocation shares among different application classes not only using history information as feedback, but also considering the different importance-levels of applications. It can adapt to the changing workload rapidly, allocate the CPU time efficiently, and furthermore, guarantee that tasks with higher level of importance get better QoS (quality of service). The experiment results show that the proposed IMAC scheme can significantly improve the efficiency of CPU utilization compared with the traditional adaptive proportional share scheduling policies.