Network connectivity under node failure
Pascal Billand,Christophe Bravard,S. Sitharama Iyengar,Rajnish Kumar,Sudipta Sarangi,Sudipta Sarangi +5 more
TL;DR: In this article, the authors examine a non-cooperative model of network formation where players may stop functioning and identify conditions under which Nash and efficient networks will remain connected after the loss of kk nodes.
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About: This article is published in Economics Letters. The article was published on 01 Dec 2016. and is currently open access. The article focuses on the topics: Node (networking) & Network formation.
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Citations
Probabilistic network values
TL;DR: This work establishes characterizations of the Myerson value and the position value for the subclass of probabilistic network games in multilinear form and shows axiomatizations based on extensions of the well-accepted properties of equal bargaining power, balanced contributions, and balanced link contributions.
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Contagion in networks: Stability and efficiency
01 Jan 2022
TL;DR: In this article , the authors study the formation of networks in environments where agents derive benefits from their neighbours (immediate links) but suffer losses through contagion when any agent on a path that connects them is hit by a shock.
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Deep Distance Sensitivity Oracles
Davin Jeong,Chau Minh Pham,Arnav Bhakta,Sarel Cohen,Maximilian Katzmann,Tobias Friedrich,Sang H. Chin +6 more
TL;DR: In this paper , the shortest path in a graph with failures consists of a concatenation of shortest paths in the original graph, and a data structure is computed that allows for fast querying of re-placement paths, typically referred to as a distance sensitivity Oracle (DSO) .
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Nash Networks with Imperfect Reliability and Heterogeneous Players
TL;DR: In this article, the authors combine the imperfect reliability model of Bala and Goyal [2000b] with the heterogeneous player model of Galeottiet et al. and compare existence, characterization and efficiency results in the resulting framework with the results in other frameworks allowing for imperfect reliability or heterogeneity.
Contagion in Networks: Stability and Efficiency
TL;DR: In this paper, the formation of networks in environments where agents derive benefits from their neighbours (immediate links) but suffer losses through contagion when any agent on a path that connects them is hit by a shock is studied.
References
Attack, Defence, and Contagion in Networks
Sanjeev Goyal,Adrien Vigier +1 more
TL;DR: It is shown that in a wide variety of circumstances a star network with all defence resources allocated to the central node is optimal for the Designer and conditions on the technology of conflict, network value function and the resource configuration for which networks with multiple hubs/components are optimal.
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original papers: A strategic analysis of network reliability
Venkatesh Bala,Sanjeev Goyal +1 more
TL;DR: If the society is large, and link formation costs are moderate, Nash networks as well as efficient networks will be ‘super-connected’ i.e. every link is redundant, which contrasts with the properties of a deterministic model of information decay, where Nash networks typically involve unique paths between agents.
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Network Vulnerability: A Designer-Disruptor Game
TL;DR: A two-stage strategic game between a network designer and a network disruptor is analyzed and general results deal with existence, uniqueness and comparative statics of Stackelberg (i.e., subgame perfect) equilibria.
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Heterogeneity and link imperfections in networks
TL;DR: It is shown that for any type of link imperfection, under heterogeneity involving only two degrees of freedom, all networks can be supported as Nash or efficient, and the earlier “anything goes” result disappears.
4
Nash networks with imperfect reliability and heterogeous players
TL;DR: It is found that non existence of Nash networks is possible in this framework even if the population is very small, compared with the framework of Haller and Sarangi [2005] which allows for heterogeneity in link reliability but assumes that players are homogeneous.