Maintaining the quality of queries over streaming data is often thought to be of tremendous challenge since data arrival rate and average per-tuple CPU processing cost are highly unpredictable. In this paper, we address a novel buffer-preposed QoS adaptation framework on the basis of control theory and present several load shedding techniques and scheduling strategies in order to guarantee the QoS of processing streaming data. As the most significant part of our framework, buffer manager consisting of scheduler, adaptor and cleaner, is deliberately introduced and analyzed. The experiments on both synthetic data and real life data show that our system, which is built by adding several concrete strategies on the framework, outperforms existing works on both resource utilization and QoS assurance.