Quantifying the Robustness of Complex Networks with Heterogeneous Nodes

Prasan Ratnayake, Sugandima Weragoda, Janaka Wansapura, Dharshana Kasthurirathna and Mahendra Piraveenan
Additional contact information
Prasan Ratnayake: Department of Physics, Faculty of Science, University of Colombo, Colombo 00700, Sri Lanka
Sugandima Weragoda: Department of Physics, Faculty of Science, University of Colombo, Colombo 00700, Sri Lanka
Janaka Wansapura: Department of Physics, Faculty of Science, University of Colombo, Colombo 00700, Sri Lanka
Dharshana Kasthurirathna: Faculty of Computing, Sri Lanka Institute of Information Technology, B263, Malabe 10115, Sri Lanka
Mahendra Piraveenan: Complex Systems Research Group, Faculty of Engineering, University of Sydney, Camperdown, NSW 2006, Australia

Mathematics, 2021, vol. 9, issue 21, 1-20

Abstract: The robustness of a complex network measures its ability to withstand random or targeted attacks. Most network robustness measures operate under the assumption that the nodes in a network are homogeneous and abstract. However, most real-world networks consist of nodes that are heterogeneous in nature. In this work, we propose a robustness measure called fitness-incorporated average network efficiency, that attempts to capture the heterogeneity of nodes using the ‘fitness’ of nodes in measuring the robustness of a network. Further, we adopt the same measure to compare the robustness of networks with heterogeneous nodes under varying topologies, such as the scale-free topology or the Erd?s–Rényi random topology. We apply the proposed robustness measure using a wireless sensor network simulator to show that it can be effectively used to measure the robustness of a network using a topological approach. We also apply the proposed robustness measure to two real-world networks; namely the C O 2 exchange network and an air traffic network. We conclude that with the proposed measure, not only the topological structure, but also the fitness function and the fitness distribution among nodes, should be considered in evaluating the robustness of a complex network.

Keywords: complex networks; network robustness; network efficiency; node heterogeneity (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2227-7390/9/21/2769/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/21/2769/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:21:p:2769-:d:669964

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().