Theoretical Computer Science and Discrete Mathematics II

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Mathematics".

Deadline for manuscript submissions: closed (20 February 2023) | Viewed by 2338

Special Issue Editors


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Departament d’Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, 43007 Tarragona, Spain
Interests: graph theory; applied mathematics; discrete mathematics; computer science
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Guest Editor
Departamento de Matemáticas, Universidad de Córdoba, Campus de Rabanales, 14071 Córdoba, Spain
Interests: graph theory; discrete mathematics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is the continuation of the previous one recently published in Symmetry (https://www.mdpi.com/journal/symmetry/special_issues/Computer_Science_Discrete_Mathematics).

The aim of this Special Issue is to attract leading researchers in different areas of discrete mathematics and theoretical computer science. To this end, it is intended to involve in this Special Issue new high-quality results on discrete mathematics including (but not limited to) graph theory, coding theory, cryptography, algorithms and complexity, discrete optimization, discrete geometry, computational geometry, topological indices, molecular descriptors, differential of graphs, metric dimension of graphs, polynomials in graphs, and alliances in graphs. The results on these topics involve their symmetry properties, both from a theoretical and an applied point of view. Contributions presented to the issue can be original research papers, short notes, or surveys.

Dr. Alejandro Estrada-Moreno
Dr. Abel Cabrera Martínez
Guest Editors

Manuscript Submission Information

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Keywords

  • graph theory
  • coding theory
  • cryptography
  • algorithms and complexity
  • discrete optimization
  • discrete geometry and computational geometry
  • topological indices and molecular descriptors
  • differential of graphs
  • metric dimension of graphs
  • polynomials and alliances in graphs

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Published Papers (2 papers)

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Research

26 pages, 7620 KiB  
Article
A New Technique to Uniquely Identify the Edges of a Graph
by Hafiz Muhammad Ikhlaq, Rashad Ismail, Hafiz Muhammad Afzal Siddiqui and Muhammad Faisal Nadeem
Symmetry 2023, 15(3), 762; https://doi.org/10.3390/sym15030762 - 20 Mar 2023
Cited by 4 | Viewed by 1981
Abstract
Graphs are useful for analysing the structure models in computer science, operations research, and sociology. The word metric dimension is the basis of the distance function, which has a symmetric property. Moreover, finding the resolving set of a graph is NP-complete, and the [...] Read more.
Graphs are useful for analysing the structure models in computer science, operations research, and sociology. The word metric dimension is the basis of the distance function, which has a symmetric property. Moreover, finding the resolving set of a graph is NP-complete, and the possibilities of finding the resolving set are reduced due to the symmetric behaviour of the graph. In this paper, we introduce the idea of the edge-multiset dimension of graphs. A representation of an edge is defined as the multiset of distances between it and the vertices of a set, BV(Γ). If the representation of two different edges is unequal, then B is an edge-multiset resolving a set of Γ. The least possible cardinality of the edge-multiset resolving a set is referred to as the edge-multiset dimension of Γ. This article presents preliminary results, special conditions, and bounds on the edge-multiset dimension of certain graphs. This research provides new insights into structure models in computer science, operations research, and sociology. They could have implications for developing computer algorithms, aircraft scheduling, and species movement between regions. Full article
(This article belongs to the Special Issue Theoretical Computer Science and Discrete Mathematics II)
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13 pages, 2515 KiB  
Article
The g-Good-Neighbor Conditional Diagnosability of Exchanged Crossed Cube under the MM* Model
by Xinyang Wang, Haozhe Li, Qiao Sun, Chen Guo, Hu Zhao, Xinyu Wu and Anqi Wang
Symmetry 2022, 14(11), 2376; https://doi.org/10.3390/sym14112376 - 10 Nov 2022
Cited by 6 | Viewed by 1421
Abstract
Diagnosability plays an important role in appraising the reliability and fault tolerance of symmetrical multiprocessor systems. The novel g-good-neighbor conditional diagnosability restrains that every fault-free node contains at least g fault-free neighbors and is suitable for large scale multiprocessor systems, attracting a [...] Read more.
Diagnosability plays an important role in appraising the reliability and fault tolerance of symmetrical multiprocessor systems. The novel g-good-neighbor conditional diagnosability restrains that every fault-free node contains at least g fault-free neighbors and is suitable for large scale multiprocessor systems, attracting a lot of research attention. The relationships between the g-good-neighbor connectivity and g-good-neighbor diagnosability of graphs under the MM* model are separately studied, but only applicable in regular graphs or just ranges rather than exact values. As a promising network structure, in 2019, Guo et al. obtained that the g-good-neighbor diagnosability of the exchanged crossed cube (ECQ(s,t)) under the PMC model is 2g(s+2g)1 (ts>g). We noticed that the exact value of the g-good-neighbor diagnosability of ECQ(s,t) under the MM* model is still to be determined. In this paper, by proving the upper and lower bounds of the g-good-neighbor diagnosability of ECQ(s,t), for the first time, we derive that the exact value of its g-good-neighbor diagnosability under the MM* model is tgm(ECQ(s,t))=2g(s+2g)1 (ts>g), achieving the unity of the g-good-neighbor diagnosability of ECQ(s, t) under both the PMC model and MM* model. Towards the end, simulation experiments are conducted to evaluate the correctness and effectiveness of our conclusion. Our research provides an important supplement to the g-good-neighbor diagnosability of ECQ(s,t). Full article
(This article belongs to the Special Issue Theoretical Computer Science and Discrete Mathematics II)
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