Edge Metric Dimension of Honeycomb and Hexagonal Networks for IoT

IF 2 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
S. Abbas, Z. Raza, Nida Siddiqui, Faheem Khan, T. Whangbo
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引用次数: 3

Abstract

: Wireless Sensor Network (WSN) is considered to be one of the fundamental technologies employed in the Internet of things (IoT); hence, enabling diverse applications for carrying out real-time observations. Robot navigation in such networks was the main motivation for the introduction of the concept of landmarks. A robot can identify its own location by sending signals to obtain the distances between itself and the landmarks. Considering networks to be a type of graph, this concept was redefined as metric dimension of a graph which is the minimum number of nodes needed to identify all the nodes of the graph. This idea was extended to the concept of edge metric dimension of a graph G , which is the minimum number of nodes needed in a graph to uniquely identify each edge of the network. Regular plane networks can be easily constructed by repeating regular polygons. This design is of extreme importance as it yields high overall performance; hence, it can be used in various networking and IoT domains. The honeycomb and the hexagonal networks are two such popular mesh-derived parallel networks. In this paper, it is proved that the minimum landmarks required for the honeycomb network HC ( n ), and the hexagonal network HX ( n ) are 3 and 6 respectively. The bounds for the landmarks required for the hex-derived network HDN 1( n ) are also proposed.
物联网蜂窝和六角形网络的边缘度量尺寸
无线传感器网络(WSN)被认为是物联网(IoT)的基础技术之一;因此,使各种应用程序进行实时观测。这种网络中的机器人导航是引入地标概念的主要动机。机器人可以通过发送信号来获取自身与地标之间的距离,从而确定自己的位置。考虑到网络是一种图,这个概念被重新定义为图的度量维度,它是识别图中所有节点所需的最小节点数。这一思想被扩展到图的边缘度量维度G的概念,它是图中唯一标识网络每条边所需的最小节点数。通过重复正多边形可以很容易地构造出正平面网络。这种设计是非常重要的,因为它产生了高的整体性能;因此,它可以用于各种网络和物联网领域。蜂窝网和六边形网是两种流行的网格衍生平行网。本文证明了蜂窝网络HC (n)和六边形网络HX (n)所需的最小地标值分别为3和6。提出了十六进制网络HDN 1(n)所需的地标边界。
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来源期刊
Cmc-computers Materials & Continua
Cmc-computers Materials & Continua 工程技术-材料科学:综合
CiteScore
5.30
自引率
19.40%
发文量
345
审稿时长
1 months
期刊介绍: This journal publishes original research papers in the areas of computer networks, artificial intelligence, big data management, software engineering, multimedia, cyber security, internet of things, materials genome, integrated materials science, data analysis, modeling, and engineering of designing and manufacturing of modern functional and multifunctional materials. Novel high performance computing methods, big data analysis, and artificial intelligence that advance material technologies are especially welcome.
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