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Distributed data centric similarity storage scheme in wireless sensor network

机译：无线传感器网络中分布式数据中心相似存储方案

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摘要

Due to the sensor hardware inaccuracy and deviation of environmental parameter, detection of imprecise data by sensor is very likely. Hence, similarity searching problem is receiving significant consideration and became an important problem to resolve. However, most of the state-of-the-art Data Centric Storage (DCS) Schemes lack optimization for similarity query of the events. This paper proposes a distributed metric based data centric similarity storage scheme (DMDCS). DMDCS takes the advantage of the idea of a vector index method, called iDistance and transforms the issue of similarity searching into the problem of interval search in one dimension. Experimental results show that DMDCS yields significant improvements on the efficiency of data querying compared with existing approaches.
机译：由于传感器硬件不准确和环境参数偏差，传感器的检测非常可能。因此，类似的搜索问题是接受重大考虑并成为解决的重要问题。然而，大多数最先进的数据中心存储（DCS）方案缺少事件的相似性查询优化。本文提出了一种基于分布式的数据中心相似存储方案（DMDC）。 DMDCS占据矢量索引方法的思想的优势，称为Invistance，并将相似性的问题转换为一个维度中的间隔搜索问题。实验结果表明，与现有方法相比，DMDC对数据查询效率的显着提高。

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