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To what extent can design principles for complex networks be derived from the study of error propagation phenomenon in smart and bio-inspired network structures?
To what extent can design principles for complex n.. (EPP)
To what extent can design principles for complex networks be derived from the study of error propagation phenomenon in smart and bio-inspired network structures?
(EPP)
Date du début: 20 août 2012,
Date de fin: 19 août 2014
PROJET
TERMINÉ
"The main subject of the proposed project is concerned with the question of whether and to what extent design principles for complex networks can be derived from the study of error propagation phenomenon (short EPP) in modern network structures found in biological, transportation and communication systems.In this project, we generalize propagation model to explicitly consider failure propagation. First of all, different classes of failures should be identified, that might affect the scenario under the examination: explosion, flood, short-circuit, fire, disease, PC-virus, etc. Then, for each one, it should be identified how it spreads with appropriate taxonomy and the graph associated with the specific class of failures. By using the global and local efficiency the effects of errors and attacks both on the global and the local properties of the network can be investigated. The crucial point is that the global organization and local modularity efficiency are extremely sensitive to the following types of errors: omission, commission, contamination and crash, which play the main role in maintaining networks’ connectivity.Five key objectives of the project are: (a) to develop a semantic network and a simulation tool for error propagation using real-time agents and example networks; (b) to perform empirical studies of example networks that enable to examine the robustness; (c) to analyse the effect of real and generated errors not only on the global properties, but also on the local properties of the network; (d) to develop and test new structures for complex systems less sensitive to errors and attacks than known structures and to measure its effects on network performance; (e) to combine results from simulations and empirical observations in order to investigate how system can be best (re)modelled to be less sensitive to errors and attacks."
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