Hu, Xiao-Bing, Wang, Ming, Leeson, Mark S., 1963-, Hines, Evor, 1957- and Di Paolo, Ezequiel. (2011) Deterministic ripple-spreading model for complex networks. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), Vol.83 (No.4). Article: 046123. ISSN 1539-3755

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Abstract

This paper proposes a deterministic complex network model, which is inspired by the natural ripple-spreading phenomenon. The motivations and main advantagesof the model are the following: (i) The establishment of many real-world networks is a dynamic process, where it is often observed that the influence of a few local events spreads out through nodes, and then largely determines the final network topology. Obviously, this dynamic process involves many spatial and temporal factors. By simulating the natural ripple-spreading process, this paper reports a very natural way to set up a spatial and temporal model for such complex networks. (ii) Existing relevant network models are all stochastic models, i.e., with a given input, they cannot output a unique topology. Differently, the proposed ripple-spreading model can uniquely determine the final network topology, and at the same time, the stochastic feature of complex networks is captured by randomly initializing ripple-spreading related parameters. (iii) The proposed model can use an easily manageable number of ripple-spreading related parameters to precisely describe a network topology, which is more memory efficient when compared with traditional adjacency matrix or similar memory-expensive data structures. (iv) The ripple-spreading model has a very good potential for both extensions and applications. ©2011 American Physical Society

Item Type:	Journal Article
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Science > Engineering
Library of Congress Subject Headings (LCSH):	Electric network topology -- Mathematical models
Journal or Publication Title:	Physical Review E (Statistical, Nonlinear, and Soft Matter Physics)
Publisher:	American Physical Society
ISSN:	1539-3755
Date:	April 2011
Volume:	Vol.83
Number:	No.4
Number of Pages:	14
Page Range:	Article: 046123
Identification Number:	10.1103/PhysRevE.83.046123
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Funder:	State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, China , International Cooperation Project "Integrated Risk Governance-Models and Modeling"
Grant number:	2010DFB20880 (International Cooperation Project "Integrated Risk Governance-Models and Modeling")
URI:	http://wrap.warwick.ac.uk/id/eprint/37195

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