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  •   Open Research
  • AUT Faculties
  • Faculty of Design and Creative Technologies (Te Ara Auaha)
  • School of Engineering, Computer and Mathematical Sciences - Te Kura Mātai Pūhanga, Rorohiko, Pāngarau
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Measuring cascade effects in interdependent networks by using effective graph resistance

Tauch, S; Liu, W; Pears, R
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Measuring%20Cascade%20Effects%20in%20Interdependent%20Networks%20by%20Using%20Effective%20Graph%20Resistance.pdf (2.802Mb)
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http://hdl.handle.net/10292/9368
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Abstract
Understanding the correlation between the underlie

network structure and overlay cascade effects in the interdependent

networks is one of major challenges in complex network

studies. There are some existing metrics that can be used

to measure the cascades. However, different metrics such as

average node degree interpret different characteristic of network

topological structure, especially less metrics have been identified

to effectively measure the cascading performance in interdependent

networks. In this paper, we propose to use a combined

Laplacian matrix to model the interdependent networks and their

interconnectivity, and then use its effective resistance metric as an

indicator to its cascading behavior. Moreover, we have conducted

extensive comparative studies among different metrics such as

average node degree, and the proposed effective resistance. We

have found that the effective resistance metric can describe more

accurate and finer characteristics on topological structure of

the interdependent networks than average node degree which

is widely adapted by the existing research studies for measuring

the cascading performance in interdependent networks.
Keywords
Interconnected networks; Network robustness; Topopogical metrics; Effective graph resistance; Average node degree; Cascade effects
Date
June 1, 2015
Source
2015 IEEE Conference on Computer Communications (INFOCOM) , 2015-04-26 to 2015-05-01, published in: 2015 IEEE Conference on Computer Communications (INFOCOM), pp.683 - 688 (6)
Item Type
Conference Contribution
Publisher
IEEE
DOI
10.1109/INFCOMW.2015.7179465
Publisher's Version
http://dx.doi.org/10.1109/INFCOMW.2015.7179465
Rights Statement
Copyright © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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