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Reducing the spectral radius of a torus network by link removal

Yang, Xiaofan, Li, Pengdeng, Yang, Lu-Xing and Wu, Yingbo 2016, Reducing the spectral radius of a torus network by link removal, PLoS One, vol. 11, no. 5, pp. 1-15, doi: 10.1371/journal.pone.0155580.

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Title Reducing the spectral radius of a torus network by link removal
Author(s) Yang, Xiaofan
Li, Pengdeng
Yang, Lu-Xing
Wu, Yingbo
Journal name PLoS One
Volume number 11
Issue number 5
Article ID e0155580
Start page 1
End page 15
Total pages 15
Publisher Public Library of Science
Place of publication San Francisco, Calif.
Publication date 2016
ISSN 1932-6203
Keyword(s) Algorithms
Computer Simulation
Monte Carlo Method
Summary The optimal link removal (OLR) problem aims at removing a given number of links of a network so that the spectral radius of the residue network obtained by removing the links from the network attains the minimum. Torus networks are a class of regular networks that have witnessed widespread applications. This paper addresses three subproblems of the OLR problem for torus networks, where two or three or four edges are removed. For either of the three subproblems, a link-removing scheme is described. Exhaustive searches show that, for small-sized tori, each of the proposed schemes produces an optimal solution to the corresponding subproblem. Monte-Carlo simulations demonstrate that, for medium-sized tori, each of the three schemes produces a solution to the corresponding subproblem, which is optimal when compared to a large set of randomly produced link-removing schemes. Consequently, it is speculated that each of the three schemes produces an optimal solution to the corresponding subproblem for all torus networks. The set of links produced by each of our schemes is evenly distributed over a network, which may be a common feature of an optimal solution to the OLR problem for regular networks.
Language eng
DOI 10.1371/journal.pone.0155580
Field of Research MD Multidisciplinary
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2016, Yang et al.
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30107776

Document type: Journal Article
Collections: School of Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.