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  1. Pubblicazioni

Network creation games with traceroute-based strategies

Articolo
Data di Pubblicazione:
2021
Citazione:
Network creation games with traceroute-based strategies / Bilò, D.; Gualà, L.; Leucci, S.; Proietti, G.. - In: ALGORITHMS. - ISSN 1999-4893. - 14:2(2021), p. 35. [10.3390/a14020035]
Abstract:
Network creation games have been extensively used as mathematical models to capture the key aspects of the decentralized process that leads to the formation of interconnected communication networks by selfish agents. In these games, each user of the network is identified by a node and selects which link to activate by strategically balancing his/her building cost with his/her usage cost (which is a function of the distances towards the other player in the network to be built). In these games, a widespread assumption is that players have a common and complete information about the evolving network topology. This is only realistic for small-scale networks as, when the network size grows, it quickly becomes impractical for the single users to gather such a global and fine-grained knowledge of the network in which they are embedded. In this work, we weaken this assumption, by only allowing players to have a partial view of the network. To this aim, we borrow three popular traceroute-based knowledge models used in network discovery: (i) distance vector, (ii) shortest-path tree view, and (iii) layered view. We settle many of the classical game theoretic questions in all of the above models. More precisely, we introduce a suitable (and unifying) equilibrium concept which we then use to study the convergence of improving and best response dynamics, the computational complexity of computing a best response, and to provide matching upper and lower bounds to the price of anarchy.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
Convergence dynamics; Local-knowledge equilibrium; Network creation games; Price of anarchy
Elenco autori:
Bilò, D.; Gualà, L.; Leucci, S.; Proietti, G.
Link alla scheda completa:
https://iris.uniss.it/handle/11388/245265
Link al Full Text:
https://iris.uniss.it//retrieve/handle/11388/245265/173095/ALGORITHMS%202021%20BIS.pdf
Pubblicato in:
ALGORITHMS
Journal
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