Edge Metric Dimension of Some Classes of Toeplitz Networks
Dalal Alrowaili, Zohaib Zahid, Muhammad Ahsan, Sohail Zafar, Imran Siddique
- Year
- 2021
- Citations
- 4
- Access
- Open access
Abstract
Toeplitz networks are used as interconnection networks due to their smaller diameter, symmetry, simpler routing, high connectivity, and reliability. The edge metric dimension of a network is recently introduced, and its applications can be seen in several areas including robot navigation, intelligent systems, network designing, and image processing. For a vertex <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>s</a:mi> </a:math> and an edge <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mi>g</c:mi> <c:mo>=</c:mo> <c:msub> <c:mrow> <c:mi>s</c:mi> </c:mrow> <c:mrow> <c:mn>1</c:mn> </c:mrow> </c:msub> <c:msub> <c:mrow> <c:mi>s</c:mi> </c:mrow> <c:mrow> <c:mn>2</c:mn> </c:mrow> </c:msub> </c:math> of a connected graph <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"> <e:mi>G</e:mi> </e:math> , the minimum number from distances of <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" id="M4"> <g:mi>s</g:mi> </g:math> with <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" id="M5"> <i:msub> <i:mrow> <i:mi>s</i:mi> </i:mrow> <i:mrow> <i:mn>1</i:mn> </i:mrow> </i:msub> </i:math> and <k:math xmlns:k="http://www.w3.org/1998/Math/MathML" id="M6"> <k:msub> <k:mrow> <k:mi>s</k:mi> </k:mrow> <k:mrow> <k:mn>2</k:mn> </k:mrow> </k:msub> </k:math> is called the distance between <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" id="M7"> <m:mi>s</m:mi> </m:math> and <o:math xmlns:o="http://www.w3.org/1998/Math/MathML" id="M8"> <o:mi>g</o:mi> </o:math> . If for every two distinct edges <q:math xmlns:q="http://www.w3.org/1998/Math/MathML" id="M9"> <q:msub> <q:mrow> <q:mi>s</q:mi> </q:mrow> <q:mrow> <q:mn>1</q:mn> </q:mrow> </q:msub> <q:mo>,</q:mo> <q:msub> <q:mrow> <q:mi>s</q:mi> </q:mrow> <q:mrow> <q:mn>2</q:mn> </q:mrow> </q:msub> <q:mo>∈</q:mo> <q:mi>E</q:mi> <q:mfenced open="(" close=")" separators="|"> <q:mrow> <q:mi>G</q:mi> </q:mrow> </q:mfenced> </q:math> , there always exists <v:math xmlns:v="http://www.w3.org/1998/Math/MathML" id="M10"> <v:msub> <v:mrow> <v:mi>w</v:mi> </v:mrow> <v:mrow> <v:mn>1</v:mn> </v:mrow> </v:msub> <v:mi>ɛ</v:mi> <v:msub> <v:mrow> <v:mi>W</v:mi> </v:mrow> <v:mrow> <v:mi>E</v:mi> </v:mrow> </v:msub> <v:mo>⊆</v:mo> <v:mi>V</v:mi> <v:mfenced open="(" close=")" separators="|"> <v:mrow> <v:mi>G</v:mi> </v:mrow> </v:mfenced> </v:math> , such that <ab:math xmlns:ab="http://www.w3.org/1998/Math/MathML" id="M11"> <ab:mi>d</ab:mi> <ab:mfenced open="(" close=")" separators="|"> <ab:mrow> <ab:msub> <ab:mrow> <ab:mi>s</ab:mi> </ab:mrow> <ab:mrow> <ab:mn>1</ab:mn> </ab:mrow> </ab:msub> <ab:mo>,</ab:mo> <ab:msub> <ab:mrow> <ab:mi>w</ab:mi> </ab:mrow> <ab:mrow> <ab:mn>1</ab:mn> </ab:mrow> </ab:msub> </ab:mrow> </ab:mfenced> <ab:mo>≠</ab:mo> <ab:mi>d</ab:mi> <ab:mfenced open="(" close=")" separators="|"> <ab:mrow> <ab:msub> <ab:mrow> <ab:mi>s</ab:mi> </ab:mrow> <ab:mrow> <ab:mn>2</ab:mn> </ab:mrow> </ab:msub> <ab:mo>,</ab:mo> <ab:msub> <ab:mrow> <ab:mi>w</ab:mi> </ab:mrow> <ab:mrow> <ab:mn>1</ab:mn> </ab:mrow> </ab:msub> </ab:mrow> </ab:mfenced> </ab:math> ; then, <ib:math xmlns:ib="http://www.w3.org/1998/Math/MathML" id="M12"> <ib:msub> <ib:mrow> <ib:mi>W</ib:mi> </ib:mrow> <ib:mrow> <ib:mi>E</ib:mi> </ib:mrow> </ib:msub> </ib:math> is named as an edge metric generator. The minimum number of vertices in <kb:math xmlns:kb="http://www.w3.org/1998/Math/MathML" id="M13"> <kb:msub> <kb:mrow> <kb:mi>W</kb:mi> </kb:mrow> <kb:mrow> <kb:mi>E</kb:mi> </kb:mrow> </kb:msub> </kb:math> is known as the edge metric dimension of <mb:math xmlns:mb="http://www.w3.org/1998/Math/MathML" id="M14"> <mb:mi>G</mb:mi> </mb:math> . In this study, we consider four families of Toeplitz networks <ob:math xmlns:ob="http://www.w3.org/1998/Math/MathML" id="M15"> <ob:msub> <ob:mrow> <ob:mi>T</ob:mi> </ob:mrow> <ob:mrow> <ob:mi>n</ob:mi> </ob:mrow> </ob:msub> <ob:mfenced open="(" close=")" separators="|"> <ob:mrow> <ob:mn>1,2</ob:mn> </ob:mrow> </ob:mfenced> </ob:math>
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992