On the metric dimension of few network sheets

F. Simon Raj, A. George
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引用次数: 1

Abstract

Let M = {v1, v2... vn} be an ordered set of vertices in a graph G (V, E). Then (d (u, v1), d (u, v2)...d (u, vn)) is called the M-coordinates of a vertex u of G. The set M is called a resolving set if the vertices of G have distinct M-coordinates. A metric basis is a resolving set M with minimum cardinality. If M is a metric basis then it is clear that for each pair of vertices u and v in the set of vertices V of G not in M, there is a vertex m in M such that the distance between u and m is not equal to the distance between v and m. The cardinality of a metric basis of G is called metric dimension. The members of a metric basis are called landmarks. A metric dimension problem is to find a metric basis. The problem of finding metric dimension is NP-Complete for general graphs. In this paper we have studied the metric dimension of a new graph called Octo-Nano windows, HDN like networks namely Equilateral Triangular Tetra sheets and Rectangular Tetra Sheet networks.
对几张网片的度量尺寸
设M = {v1, v2,…是图G (V, E)中顶点的有序集合,则(d (u, v1), d (u, v2)…d (u, vn))称为G的顶点u的M坐标,如果G的顶点具有不同的M坐标,则集合M称为解析集。度量基是具有最小基数的解析集M。如果M是一个度量基,那么很明显,对于不在M中的G的顶点v集合中的每一对顶点u和v, M中存在一个顶点M,使得u和M之间的距离不等于v和M之间的距离。G的度量基的基数称为度量维数。度规基的成员称为地标。一个度量维数问题就是找到一个度量基。对于一般图,度量维的求值问题是np完全的。在本文中,我们研究了一种称为八纳米窗口的新图的度量维度,HDN网络即等边三角形四片和矩形四片网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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