Robustness of networks – a Swiss perspective

Hans Jürgen Herrmann, theoretical physicist and professor at ETH Zürich, presents various strategies of optimizing the robustness of networks as part of our risk management lecture series.

Event Details

Location

swissnex India
#26, Rest House Crescent Road, Bangalore, Karnataka 560001 India

Date

February 18, 2016 from 6:30 pm to 9:00 pm

swissnex India invites Hans Herrmann, theoretical physicist and professor at ETH Zürich, to discuss prevention of destruction of networks and applications to power them. The lecture is co-organized by swissnex India and Swiss Re India to provide high-level inputs on risk to inspire peers, future leaders, and potential partners.

Meet the Speaker –

Prof. Herrmann holds a PhD in statistical physics from Cologne and is a member of CNRS at the Service de Physique Théorique in Saclay (France). Earlier he worked at HLRZ of KFA Jülich (Germany), was a professor and director of the PMMH of ESPCI, Paris and the Institute of Computer Physics at the University of Stuttgart (Germany). He also worked at the Institute of Building Materials at ETH Zürich (Switzerland). He is a Guggenheim Fellow (1986), member of the Brazilian Academy of Science, Max-Planck prize recipient (2002) and Gentner-Kastler prize (2004); ERC Advanced (2012); managing editor of International Journal of Modern Physics C and of Granular Matter and member of several editorial boards and committees including the Research Commission of ETH; author of about 570 publications and co-editor of 13 books.
Prof. Hans Herrmann
Theoretical Physicist and Professor / ETH Zürich

 

Abstract of the presentation –

The Internet, protein interactions or social organizations are examples for complex networks. Such networks typically cease to be operational when they fall apart in disconnected pieces. Destruction can happen randomly or due to a malicious attack. I will present various strategies of optimizing the robustness of networks preserving some of their properties as for instance their degree distribution. Artificial networks like the Apollonian network can serve to systematically investigate the optimization process. The optimized networks exhibit a novel “onion-like” topology. Applications to power networks, botnets, road systems and brain models will be discussed. Particularly dramatic failures occur when two networks are coupled, like for example the electric grid and the communication network. The abruptness in the connectivity at collapse can be attenuated through autonomous nodes and I will discuss strategies to optimize the choice of these nodes.

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