scholarly journals Metric dimension of critical Galton–Watson trees and linear preferential attachment trees

2021 ◽  
Vol 95 ◽  
pp. 103317
Author(s):  
Júlia Komjáthy ◽  
Gergely Ódor
Keyword(s):  
Preferential Attachment ◽  
Metric Dimension

Models of network formation

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Degree Distribution ◽  
Network Formation ◽  
Preferential Attachment ◽  
Network Size ◽  
Large Network ◽  
Citation Networks ◽  
Airline Networks ◽  
Attachment Model ◽  
Delivery Networks

This chapter describes models of the growth or formation of networks, with a particular focus on preferential attachment models. It starts with a discussion of the classic preferential attachment model for citation networks introduced by Price, including a complete derivation of the degree distribution in the limit of large network size. Subsequent sections introduce the Barabasi-Albert model and various generalized preferential attachment models, including models with addition or removal of extra nodes or edges and models with nonlinear preferential attachment. Also discussed are node copying models and models in which networks are formed by optimization processes, such as delivery networks or airline networks.

scholarly journals Power graphs and exchange property for resolving sets

2019 ◽  
Vol 17 (1) ◽  
pp. 1303-1309 ◽  
Author(s):  
Ghulam Abbas ◽  
Usman Ali ◽  
Mobeen Munir ◽  
Syed Ahtsham Ul Haq Bokhary ◽  
Shin Min Kang
Keyword(s):  
Present Article ◽  
Linear Algebra ◽  
Finite Groups ◽  
Robot Navigation ◽  
Simple Graph ◽  
Exchange Property ◽  
Metric Dimension ◽  
Sufficient Condition ◽  
Resolving Set ◽  
Dihedral Groups

Abstract Classical applications of resolving sets and metric dimension can be observed in robot navigation, networking and pharmacy. In the present article, a formula for computing the metric dimension of a simple graph wihtout singleton twins is given. A sufficient condition for the graph to have the exchange property for resolving sets is found. Consequently, every minimal resolving set in the graph forms a basis for a matriod in the context of independence defined by Boutin [Determining sets, resolving set and the exchange property, Graphs Combin., 2009, 25, 789-806]. Also, a new way to define a matroid on finite ground is deduced. It is proved that the matroid is strongly base orderable and hence satisfies the conjecture of White [An unique exchange property for bases, Linear Algebra Appl., 1980, 31, 81-91]. As an application, it is shown that the power graphs of some finite groups can define a matroid. Moreover, we also compute the metric dimension of the power graphs of dihedral groups.

scholarly journals Metric Dimension Parameterized By Treewidth

Algorithmica ◽  
2021 ◽  
Author(s):  
Édouard Bonnet ◽  
Nidhi Purohit
Keyword(s):  
Computable Function ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Minimum Size ◽  
Metric Dimension ◽  
Resolving Set ◽  
Input Graph ◽  
Outerplanar Graphs ◽  
Bounded Treewidth ◽  
Fpt Algorithm

AbstractA resolving set S of a graph G is a subset of its vertices such that no two vertices of G have the same distance vector to S. The Metric Dimension problem asks for a resolving set of minimum size, and in its decision form, a resolving set of size at most some specified integer. This problem is NP-complete, and remains so in very restricted classes of graphs. It is also W[2]-complete with respect to the size of the solution. Metric Dimension has proven elusive on graphs of bounded treewidth. On the algorithmic side, a polynomial time algorithm is known for trees, and even for outerplanar graphs, but the general case of treewidth at most two is open. On the complexity side, no parameterized hardness is known. This has led several papers on the topic to ask for the parameterized complexity of Metric Dimension with respect to treewidth. We provide a first answer to the question. We show that Metric Dimension parameterized by the treewidth of the input graph is W[1]-hard. More refinedly we prove that, unless the Exponential Time Hypothesis fails, there is no algorithm solving Metric Dimension in time $$f(\text {pw})n^{o(\text {pw})}$$ f ( pw ) n o ( pw ) on n-vertex graphs of constant degree, with $$\text {pw}$$ pw the pathwidth of the input graph, and f any computable function. This is in stark contrast with an FPT algorithm of Belmonte et al. (SIAM J Discrete Math 31(2):1217–1243, 2017) with respect to the combined parameter $$\text {tl}+\Delta$$ tl + Δ , where $$\text {tl}$$ tl is the tree-length and $$\Delta$$ Δ the maximum-degree of the input graph.

scholarly journals Mixed metric dimension of graphs with edge disjoint cycles

2021 ◽  
Vol 300 ◽  
pp. 1-8
Author(s):  
Jelena Sedlar ◽  
Riste Škrekovski
Keyword(s):  
Metric Dimension ◽  
Edge Disjoint ◽  
Disjoint Cycles ◽  
Mixed Metric

scholarly journals The structure of co-publications multilayer network

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ghislain Romaric Meleu ◽  
Paulin Yonta Melatagia
Keyword(s):  
Power Law ◽  
Degree Distribution ◽  
Preferential Attachment ◽  
Small World ◽  
Generation Model ◽  
Small World Network ◽  
Power Law Distribution ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Scientific Papers

AbstractUsing the headers of scientific papers, we have built multilayer networks of entities involved in research namely: authors, laboratories, and institutions. We have analyzed some properties of such networks built from data extracted from the HAL archives and found that the network at each layer is a small-world network with power law distribution. In order to simulate such co-publication network, we propose a multilayer network generation model based on the formation of cliques at each layer and the affiliation of each new node to the higher layers. The clique is built from new and existing nodes selected using preferential attachment. We also show that, the degree distribution of generated layers follows a power law. From the simulations of our model, we show that the generated multilayer networks reproduce the studied properties of co-publication networks.

scholarly journals Visualizing Spatial Economic Supply Chains to Enhance Sustainability and Resilience

2021 ◽  
Vol 13 (3) ◽  
pp. 1512
Author(s):  
Yicheol Han ◽  
Stephan J. Goetz ◽  
Claudia Schmidt
Keyword(s):  
Supply Chains ◽  
Preferential Attachment ◽  
Material Balance ◽  
Service Industries ◽  
Firm Location ◽  
Commodity Flows ◽  
Geographic Space ◽  
Different Types ◽  
Gravity Equations ◽  
General Method

This article presents a spatial supply network model for estimating and visualizing spatial commodity flows that used data on firm location and employment, an input–output table of inter-industry transactions, and material balance-type equations. Building on earlier work, we proposed a general method for visualizing detailed supply chains across geographic space, applying the preferential attachment rule to gravity equations in the network context; we then provided illustrations for U.S. extractive, manufacturing, and service industries, also highlighting differences in rural–urban interdependencies across these sectors. The resulting visualizations may be helpful for better understanding supply chain geographies, as well as business interconnections and interdependencies, and to anticipate and potentially address vulnerabilities to different types of shocks.

scholarly journals Scale free is not rare in international trade networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Linqing Liu ◽  
Mengyun Shen ◽  
Chang Tan
Keyword(s):  
International Trade ◽  
Preferential Attachment ◽  
Developed Countries ◽  
Total Trade ◽  
Trade Networks ◽  
Scale Free ◽  
Weighted Networks ◽  
Free Exploration ◽  
Technology Products ◽  
Attachment Mechanism

AbstractFailing to consider the strong correlations between weights and topological properties in capacity-weighted networks renders test results on the scale-free property unreliable. According to the preferential attachment mechanism, existing high-degree nodes normally attract new nodes. However, in capacity-weighted networks, the weights of existing edges increase as the network grows. We propose an optimized simplification method and apply it to international trade networks. Our study covers more than 1200 product categories annually from 1995 to 2018. We find that, on average, 38%, 38% and 69% of product networks in export, import and total trade are scale-free. Furthermore, the scale-free characteristics differ depending on the technology. Counter to expectations, the exports of high-technology products are distributed worldwide rather than concentrated in a few developed countries. Our research extends the scale-free exploration of capacity-weighted networks and demonstrates that choosing appropriate filtering methods can clarify the properties of complex networks.

scholarly journals Likelihood-based approach to discriminate mixtures of network models that vary in time

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Naomi A. Arnold ◽  
Raul J. Mondragón ◽  
Richard G. Clegg
Keyword(s):  
Network Model ◽  
Change Point ◽  
Network Science ◽  
Preferential Attachment ◽  
Network Models ◽  
Explanatory Models ◽  
Growth Mechanisms ◽  
Artificial Data ◽  
Network Growth ◽  
Over Time

AbstractDiscriminating between competing explanatory models as to which is more likely responsible for the growth of a network is a problem of fundamental importance for network science. The rules governing this growth are attributed to mechanisms such as preferential attachment and triangle closure, with a wealth of explanatory models based on these. These models are deliberately simple, commonly with the network growing according to a constant mechanism for its lifetime, to allow for analytical results. We use a likelihood-based framework on artificial data where the network model changes at a known point in time and demonstrate that we can recover the change point from analysis of the network. We then use real datasets and demonstrate how our framework can show the changing importance of network growth mechanisms over time.

Metric and Strong Metric Dimension in Cozero-Divisor Graphs

2021 ◽  
Vol 18 (3) ◽  
Author(s):  
R. Nikandish ◽  
M. J. Nikmehr ◽  
M. Bakhtyiari
Keyword(s):  
Metric Dimension ◽  
Strong Metric Dimension

What Influences Relationship Formation in a Global Civil Society Network? An Examination of Valued Multiplex Relations

2021 ◽  
pp. 009365022110161
Author(s):  
Adam J. Saffer ◽  
Andrew Pilny ◽  
Erich J. Sommerfeldt
Keyword(s):  
Communication Network ◽  
Civil Society ◽  
Real World ◽  
Network Formation ◽  
Preferential Attachment ◽  
Interorganizational Networks ◽  
Communication Research ◽  
Relationship Formation ◽  
Interorganizational Communication ◽  
Strength Of Ties

Recent interorganizational communication research has taken up the question: why are networks structured the way they are? This line of inquiry has advanced communication network research by helping explain how and why networks take on certain structures or why certain organizations become positioned advantageously (or not). Yet, those studies assume relationships among organizations are either present or absent. This study considers how the strength of ties and multiplex relationships among organizations may reveal a more complex explanation for why networks take on certain structures. Our results challenge some long held assumptions about the mechanisms that influence network formation. For instance, our results offer important insights into the consequences of closure mechanisms, the applicability of preferential attachment to real-world networks, and the nuances of homophily in network formation on multidimensional relationships in a communication network. Implications for interorganizational networks are discussed.

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