Network robustness improvement via long-range links | Marco Grassia

Network robustness improvement via long-range links

Abstract

Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what extent a network keeps working when failures occur in its structure and how disruptions can be avoided. In this paper, we introduce the idea of exploiting long-range links to improve the robustness of Scale-Free (SF) networks. Several experiments are carried out by attacking the networks before and after the addition of links between the farthest nodes, and the results show that this approach effectively improves the SF network correct functionalities better than other commonly used strategies.

Publication
Computational Social Networks
Marco Grassia
Marco Grassia
Research Fellow · Network Science and Machine Learning

Research Fellow in Network Science and Machine Learning at University of Catania

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