A data aggregation arithmetic based on directed diffusion and batch estimate is proposed which inte-grate the data of multi-sensors for watching one object to improve the precision of the data and reduce the data stream to decrease energy consumption. 针对这个问题提出一种基于定向扩散与分批估计的数据融合算法,对监测同一对象的多个传感器所采集的数据进行综合,提高数据精度和可信度,并减少数据传输量,从而降低了功耗。
Taking into account the basic characteristics of the data flow velocity, based on the "time window" concept, the batch processing ideas are used to handle data stream tuples, to reduce the scheduling switch overhead and to improve system performance. 考虑到数据流流速的基本特征,本文在基于时间窗口概念的基础上批处理数据流元组,以减少调度切换开销,提高系统性能。
This paper proposed solutions and main conclusion for other domestic many varieties and small batch, short delivery clothing enterprise the implement of lean production and value stream management has the outstanding theoretical significance and practical value. 本文所提出的解决方案和主要结论对于国内其他多品种,小批量,短交期的服装企业实施精益生产和价值流管理具有突出的理论意义和实用价值。