物联网传感器节点定位的最短路径算法

Ajay Kumar, V. Jain, P. Bhattacharya
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引用次数: 0

摘要

物联网由于其在各个领域的应用而引起了研究人员和其他学术界的兴趣。在由多个传感器和智能设备组成的指定区域内确定传感器节点的位置至关重要,这需要设备与传感器节点之间的关联[1]。本地化是任何智能网络的通信、集群、分布、路由等其他服务的基本要求。多维尺度是传感器节点定位的有效方法之一。该方法利用获取传感器对之间最小距离路径的过程,有助于估计节点的相对位置。本文对不同类型的最短路径算法进行了说明和比较。然后,我们讨论了在智能网络中使用多维尺度过程来获得节点的绝对位置,并减少了误差累积。对于无线传感器网络和物联网来说,必须有一个高效、经济和可扩展的传感器节点位置估计过程。实验结果证明了所讨论的方法在各种路由、拓扑和区域的物联网中应用的效率和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Shortest Path Algorithms for Sensor Node Localization for Internet of Things
Internet of Things have gained the interest of researchers and other academic communities due to their applications in various fields. Determining the location of a sensor node within the specified area consisting of number of sensors and smart devices is very crucial, which requires association between the devices and the sensor nodes[1]. Localization is the basic requirement for other services of any smart network like communication, clustering, distribution, routing etc. Multidimensional scaling is one of the approach used effectively for the sensor node localization. In this approach the process to obtain the minimum distance path between the pair of sensors are used which helps in estimating the relative positions of the nodes. This paper includes the explanation and comparison of different types shortest path algorithms. Then, we discuss about the use of multidimensional scaling process to obtain the absolute positions of nodes with reduced error cumulation in a smart network. It is mandatory to have a efficient, economic and scalable sensor node position estimation process for a wireless sensor network and hence for internet of Things. The results obtained experimentally proves the efficiency and effectiveness of the methods discussed for use in Internet of Things with various routing, topology and area.
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