Abstract. Unlike processing snapshot queries in a traditional DBMS, the processing of continuous queries in a data stream management system (DSMS) needs to satisfy quality requirements such as processing delay. When the system is overloaded, quality degrades significantly thus load shedding becomes necessary. Maintaining the quality of queries is a difficult problem because both the processing cost and data arrival rate are highly unpredictable. We propose a quality adaptation framework that adjusts the application behavior based on the current system status. We leverage techniques from the area of control theory in designing the quality adaptation framework. Our simulation results demonstrate the effectiveness of the control-based quality adaptation strategy. Comparing to solutions proposed in previous works, our approach achieves significantly better quality with less waste of resources.
This paper proposes a weaving design method to optimize the loading capability of microcapsule fabrics of yarns and fabrics, with moxa oil. A complex coacervation method was employed to prepare the moxa oil microcapsules by using gelatin-Arabic gum as wall material. The methods of orthogonal experimental design and analysis of range were used. The woven structure, weft yarn density, and weft yarn count were determined as the most important factors affecting the moxa oil content of microcapsule fabrics. Nine fabric specimens with respect to L9 (34) orthogonal design were woven and treated with a moxa oil microcapsule. By the experiment results, the woven structure was found to be the factor that has the most significant effect on the microcapsule content of woven fabrics. In addition, the optimum fabric configuration satisfying the maximum content of the moxa oil microcapsule was determined as A3B1C3, which corresponds to a honeycomb structure of woven structure, 230 no./10 cm of weft yarn density and 10s of weft yarn count.
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