InterJournal Complex Systems, 515 Status: Accepted |
Manuscript Number: [515] Submission Date: 20430 Revised On: 20508 |
RAn (Robustness Analyser) |
Subject(s): CX.64, CX.07
Category: Brief Article
Abstract:
RAn (Robustness Analyser) Robustness of complex networks has been extensively discussed in the scientific literature for the last few years. Several authors have pointed out that different topologies would react differently to node failure and/or broken links (see e.g. Albert et al., 2000; Cohen et al., 2000) and that mathematical techniques used in statistical physics could effectively be used to describe their behaviour (see e.g. Callaway et al., 2000). It has also been demonstrated that most artificial networks, including the Internet and the World Wide Web, can be described as complex systems, often featuring "scale-free" properties (see e.g. Albert et al., 1999; Faloutsos et al., 1999; Tadic, 2001). In this context, it is becoming increasingly obvious that the robustness of a wide variety of real distributed architectures (telecommunication and transportation networks, power grids etc.) is essentially a function of their topology, and could therefore be evaluated on the basis of their blueprint. Similarly, several alternative designs could be compared before their actual implementation, in order, for example, to balance redundancy costs against increased resilience. RAn is the software embodiment of a mathematical framework developed to quantify complex networks' behaviour when submitted to cumulative node failure. It is designed to test the robustness of any given network topology in an automated fashion, computing the values for a set of global variables after performing a statistical analysis of simulation results. Those variables, characterising the decay of the network's largest component, effectively summarise the system's resilience to this form of stress.
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