Designing virus-resistant networks

A game-formation approach

Conference Paper (2015)
Author(s)

S. Trajanovski (TU Delft - Network Architectures and Services)

F.A. Kuipers (TU Delft - Network Architectures and Services)

Yezekael Hayel (University of Avignon)

Eitan Altman (INRIA Sophia Antipolis )

P.F.A. Van Mieghem (TU Delft - Network Architectures and Services)

Research Group
Network Architectures and Services
Copyright
© 2015 S. Trajanovski, F.A. Kuipers, Yezekael Hayel, Eitan Altman, P.F.A. Van Mieghem
DOI related publication
https://doi.org/10.1109/CDC.2015.7402216
More Info
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Publication Year
2015
Language
English
Copyright
© 2015 S. Trajanovski, F.A. Kuipers, Yezekael Hayel, Eitan Altman, P.F.A. Van Mieghem
Research Group
Network Architectures and Services
Pages (from-to)
294-299
ISBN (electronic)
978-1-4799-7886-1
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Abstract

Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate τ, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of τ, trees different from the path and star graphs may be optimal.






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