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Complex Event Detection for Long Process

机译:复杂事件检测,适用于长流程

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The traditional CED (Complex Event Detection) methods were achieved in memory by creating a data structure. But the memory will become a choke-point for the huge data structure when orienting long process and numerous data. So large amounts of data must be stored in external memory, and transferred to memory when needed. In this paper, we present TSH (Hash by object ID based on time slice model) storage strategy and instance map structure to ensure small I/O cost when transferring instances needed to memory. In addition, we also propose an incremental method to accelerate the matching process. Finally, the validity of the methods presented in this paper is proved by experiments on simulated data sets.
机译:传统的CED(复杂事件检测)方法是通过创建数据结构在内存中实现的。但是,当定向长流程和大量数据时,内存将成为庞大数据结构的瓶颈。因此必须将大量数据存储在外部存储器中,并在需要时传输到存储器中。在本文中,我们提出了TSH(基于时间片模型的按对象ID的哈希)存储策略和实例映射结构,以确保在将所需的实例传输到内存时确保较小的I / O成本。此外,我们还提出了一种增量方法来加快匹配过程。最后,通过对模拟数据集的实验证明了本文提出的方法的有效性。

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