数据流QoS自适应框架聚集查询卸载策略的研究

his paper studies the load shedding for aggregation queries over the data streams, which is based on the control-based QoS adaptation framework. In the case of that the CPU capacity is limited and the memory is over loaded, this technique sheds load from memory in aggregation operation, meanwhile, promising a proper QoS. As there is a single aggregation or several aggregation operations, this technique extends the existed framework to an advanced one which can get the subset of the accurate result instead of getting the approximate ones. It keeps the original components such as the cleaner, scheduler and the load shedder, but also extends the load shedder part. Further, adding new components called window-distributor and aggregate-operator to the frame, to promise the accurateness of the result. It combines the new strategy to the existed frame to make sure that the system can be adaptive in dynamic environments when processing the aggregation queries. The experiments show that the system is outperforms other existing ways on resource utilization and deadline miss ratio.