Book Review: Evolution and Structure of the Internet: A Statistical Physics Approach.

By Gábor Szabó. 2006

417 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/bfc365c5fd5eb3d2358d8ce122c287bb515cb589

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Citations in the corpus

Robustness of cooperation in the evolutionary prisoner's dilemma on complex networks (2007, background): “Simply said, the clustering of cooperators in the lattice could provide high enough fitness to the cooperator nodes expos d to invasion, to the extent of preserving cooperators from evolutionary extinction, even when defection is blatantly favored by the one-shot (two-players) game analysis.”
Modeling bursts and heavy tails in human dynamics (2005, background): “Subcritical regime, ρ ≪ 1: If the arrival rate of the tasks is much smaller than the execution rate, the fact that the queue length has an upper bound has little significance, sinceℓ will rarely reach its upper boundL, but will fluctuate in the vicinity of ℓ = 0.”
Cascade of failures in coupled network systems with multiple support-dependent relations (2010, background): “The dependency relation is represented by a link connecting the support node in one network and the dependent node in the other network (“inter-links”).”
Activity driven modeling of time varying networks (2012, background): “Connectivity-driven network models are well-suited for capturing the essential features of systems such as the Internet, where connections among nodes are long-lived elements [18, 19].”
Characterization and modeling of weighted networks (2004, background): “We then present two case studies, the airline connection network and the scientific collaboration network, which are representative of critical infrastructures and social systems, respectively.”
Statistical physics of social dynamics (2007, background): “More precisely, the degree distribution of the second is kP (k)/〈k〉 (Pastor-Satorras and Vespignani, 2004).”
The Matthew effect in empirical data (2014, background): “The Gibrat law of proportional growth [30], inspired by the assumption that the size of an enterprize and its growth are interdependent, also predates the formal introduction of the Matthew effect.”
Control Principles of Complex Networks (2015, background): “a communication network (Pastor-Satorras and Vespignani, 2004), or transcription factor concentration in a gene regulatory network (Lezon et al.”
Apollonian networks: simultaneously scale-free, small world, euclidean, space filling, and with matching graphs. (2004, background): “Many network types have been proposed and investigated serving to differentiate and elucidate effects ranging from clan formation, epidemics spreading, and logistic planning to earthquake prediction, neural activity, and immunological defenses [1–4].”
Interdependent networks: reducing the coupling strength leads to a change from a first to second order percolation transition. (2010, background): “Most of the research on networks has concentrated on the limited case of a single network [1–5] while real world systems are composed frommany interdependent networks that interact with one another [6–8].”
Cache "less for more" in information-centric networks (extended version) (2012, background): “Readers can find related discussions in [39,46].”