基于MapReduce的火区地磁定位并行算法

Wang Tao, Haiyan Zeng, Shenghui Zhao
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引用次数: 0

摘要

传统的地磁指纹定位都采用串行算法,通过对由地球磁场产生的室内地磁大数据进行两两比对来实现。该系统在处理海量智能手机位置数据时存在瓶颈。本文提出了一种新的基于Hadoop-MapReduce的方法,可以看作是一种并行算法。通过引入更多的计算机,该方法可以大大提高室内地磁定位的性能。同时,采用动态时空窗来提高检测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parallel Algorithm of Geomagnetic Localization in Fire Compartment Based on MapReduce
All Traditional geomagnetic fingerprint location is characterized by serial algorithm, which is realized through pair-wise comparison in in-door Geomagnetic big data which is generated by earth's magnetic field. The system is bottle-necked when processing massive smart phone location data. In this paper, a new Hadoop-MapReduce based method is put forward, which can be seen as a parallel algorithm. Through introducing more computers, the new method can greatly enhance the performance of in-door geomagnetic localization. In the meantime, a dynamic spatial-temporal window is used to promote the detecting accuracy.
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