基于空间相关性的物联网设备级聚类

Anubhav Shivhare, M. Maurya, Vatsal J. Sanglani, Manish Kumar
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引用次数: 0

摘要

物联网的出现开启了一个时代,人们需要新的智能方案来管理网络,而不影响网络的生命周期。网络中传感器节点的聚类在物联网中起着至关重要的作用。基于传感器节点之间的距离对传感器节点进行聚类,以优化网络的生存期,提出了许多研究工作。此外,最近的进展并没有关注传感器粒子的空间相关信息及其位置信息。提出了一种多模态物联网网络中考虑空间信息的设备级聚类方案。因此,研究工作强调了基于空间相关性的聚类方法的重要性。此外,使用标准相关度量,如Pearson’s、Kendall’s和Spearman’s相关来评估所提出方案的性能。通过对集群成员节点偏差的比较,验证了该方案在负载均衡中的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial Correlation Based Device Level Clustering for IoT
The advent of IoT has ushered an era of demands for new and intelligent schemes to manage the network without compromising on the network lifetime. Clustering of sensor motes in a network plays a vital role in IoT. Many research works are proposed for clustering the sensor motes based on the distance between each sensor motes to optimize the network lifetime. Moreover, recent advancements do not focus on spatial correlation information of a sensor mote along with its location information. The authors propose a novel scheme for device level clustering in multi-modal IoT network which takes spatial information into account for clustering of devices. Thus the research work highlights the importance of clustering methodology based on spatial correlation. Further, standard correlation metrices like Pearson's, Kendall's and Spearman's correlation were used to evaluate the performance of the proposed scheme. A comparison of deviation in cluster member nodes is also done to show the effectiveness of the scheme in load balancing.
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