入侵者监控系统中高度滤波的几何算法

Jaeseok Shim, Yujin Lim, Jaesung Park
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引用次数: 0

摘要

无线传感器网络(WSN)已被用于监控应用。然而,由于资源的限制,对大量传感器数据的有效管理是一个重要的问题。近年来,云计算已经成为一种新的计算范式,可以按需提供可靠的资源、软件和数据。它将大量资源整合到无线传感器网络中,以创新许多新服务。本文设计了一个基于云平台的入侵监控系统。在该系统中,我们提出了一种几何算法来进行语义过滤,以去除无意义的数据并减少云存储中的数据量。通过各种环境下的实验,我们证明了算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Geometric algorithm for height filtering in intruder monitoring system
Wireless Sensor Network (WSN) has been used for monitoring applications. However, due to the limitation of resources, efficient management of the large volume of sensor data is an important issue to deal with. In recent years, cloud computing has emerged as a new computing paradigm to provide reliable resources, software, and data on demand. It integrates its lots of resources into WSNs to innovate a number of new services. In this paper, we design an intruder monitoring system on top of a cloud platform. In the system, we propose a geometric algorithm for semantic filtering in order to remove meaningless data and reduce the volume of data stored in cloud storages. Through experiments in various environments, we show the performance of our algorithm.
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