Abstract
Cascading failures in many systems such as infrastructures or financial networks can lead to catastrophic system collapse. We develop here an intuitive, powerful and simple-to-implement approach for mitigation of cascading failures on complex networks based on local network structure. We offer an algorithm to select critical nodes, the protection of which ensures better survival of the network. We demonstrate the strength of our approach compared to various standard mitigation techniques. We show the efficacy of our method on various network structures and failure mechanisms, and finally demonstrate its merit on an example of a real network of financial holdings.
Highlights
Cascading failures in many systems such as infrastructures or financial networks can lead to catastrophic system collapse
We find that our protection, even with partial information, is highly efficient in mitigating the cascading failure process
In order to be selected, the nodes must be fragile under a relevant failure mechanism, as per the definition in “Mitigation strategy”, and they need to have a sufficient amount of fragile neighbors
Summary
Cascading failures in many systems such as infrastructures or financial networks can lead to catastrophic system collapse. We develop here an intuitive, powerful and simple-to-implement approach for mitigation of cascading failures on complex networks based on local network structure. Determining whether the system is in a state where small, local failures could spread globally, and lead to a system-wide collapse may be impossible without precise knowledge of system variables and parameters. This precise knowledge is rarely attainable in real life dynamics. An exhaustive analysis of all variants is impossible, so we choose relatively simple but broadly applicable models with several variants and offer non-trivial insights on mitigating cascading failures based on local neighborhoods information. Cascading processes on networks may either be the goal, such as in the context of marketing and advertising, where the target may be to optimally disseminate information across networks[6,7,8,9], or an adverse result (Fig. 1), e.g. in finance, health care or infrastructures, where cascading process of failure or disease spreading is detrimental, and should ideally be avoided, mitigated or stopped
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