Designing virus-resistant networks: A game-formation approach

Stojan Trajanovski, Fernando A. Kuipers, Yezekael Hayel, Eitan Altman, Piet Van Mieghem

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

5 Citations (Scopus)
132 Downloads (Pure)


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.

Original languageEnglish
Title of host publicationProceedings of the 2015 IEEE 54th Annual Conference on Decision and Control, CDC'15
EditorsY. Ohta, M. Sampei, A. Astolfi
Place of PublicationPiscataway, NJ
Number of pages6
ISBN (Electronic)978-1-4799-7886-1
Publication statusPublished - Dec 2015
Event54th IEEE Conference on Decision and Control, CDC 2015 - Osaka, Japan
Duration: 15 Dec 201518 Dec 2015
Conference number: 54


Conference54th IEEE Conference on Decision and Control, CDC 2015
Abbreviated titleCDC 2015


  • Games
  • Nash equilibrium
  • Viruses (medical)
  • Network topology
  • Peer-to-peer computing
  • Stability analysis
  • Security


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