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SMALL-WORLD EFFECT IN GEOGRAPHICAL ATTACHMENT NETWORKS

Part of: Operations research and management science Graph theory Markov processes

Published online by Cambridge University Press:  12 September 2019

Qunqiang Feng ,
Yongkang Wang  and
Zhishui Hu Open the ORCID record for Zhishui Hu [Opens in a new window]
Qunqiang Feng
Affiliation:
Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, 230026, China E-mails: fengqq@ustc.edu.cn; tjwyk@mail.ustc.edu.cn; huzs@ustc.edu.cn
Yongkang Wang
Affiliation:
Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, 230026, China E-mails: fengqq@ustc.edu.cn; tjwyk@mail.ustc.edu.cn; huzs@ustc.edu.cn
Zhishui Hu
Affiliation:
Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, 230026, China E-mails: fengqq@ustc.edu.cn; tjwyk@mail.ustc.edu.cn; huzs@ustc.edu.cn
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Abstract

In this work, we use rigorous probabilistic methods to study the asymptotic degree distribution, clustering coefficient, and diameter of geographical attachment networks. As a type of small-world network model, these networks were first proposed in the physical literature, where they were analyzed only with heuristic arguments and computational simulations.

Keywords

degree distributiondiametergeographical attachmentrandom networkssmall-world

MSC classification

Primary: 05C80: Random graphs 90B15: Network models, stochastic
Secondary: 60J85: Applications of branching processes
Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 35 , Issue 2 , April 2021 , pp. 276 - 296
Copyright
Copyright © Cambridge University Press 2019

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