Title :
Network robustness and topological characteristics in scale-free networks
Author :
Kasthurirathna, Dharshana ; Piraveenan, Mahendra ; Thedchanamoorthy, Gnana
Author_Institution :
Centre for Complex Syst. Res., Univ. of Sydney, Sydney, NSW, Australia
Abstract :
In this paper, we explore the relationship between the topological characteristics of a complex network and its robustness to sustained targeted attacks. Using synthesized scale-free networks, we look at a number of network measures, including rich club profiles, scale-free exponent, modularity, assortativity, average path length and clustering coefficient of a network, and how each of these influence the robustness of a scale-free network under targeted attacks. We consider sustained targeted attacks by order of node degree. We show that assortativity and average path length have a positive correlation with network robustness, whereas clustering coefficient has a negative correlation. We did not find any correlation between the modularity and robustness, scale-free exponent and robustness, or rich-club profiles and robustness. Our results highlight the importance of topological characteristics in influencing network robustness, and illustrate design strategies network designers can use to increase the robustness of scale-free networks under sustained targeted attacks.
Keywords :
complex networks; correlation theory; network theory (graphs); network topology; assortativity; clustering coefficient; complex network; correlation theory; network design strategy; network measure; network robustness; node degree; rich club profile; scale-free exponent; scale-free network; sustained targeted attack; topological characteristics; Adaptive systems; Complex networks; Conferences; Correlation; Intelligent systems; Measurement; Robustness;
Conference_Titel :
Evolving and Adaptive Intelligent Systems (EAIS), 2013 IEEE Conference on
Conference_Location :
Singapore
DOI :
10.1109/EAIS.2013.6604114