About: Local World Evolving Network Models

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Evolving networks are dynamic networks that change through time. In each period there are new nodes and edges that join the network while the old ones disappear. Such dynamic behaviour is characteristic for most real-world networks, regardless of their range - global or local. However, networks differ not only in their range but also in their topological structure. It is possible to distinguish: * Random networks * Free- scale networks * Small-world networks * Local-world networks

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rdfs:label	Local World Evolving Network Models (en)
rdfs:comment	Evolving networks are dynamic networks that change through time. In each period there are new nodes and edges that join the network while the old ones disappear. Such dynamic behaviour is characteristic for most real-world networks, regardless of their range - global or local. However, networks differ not only in their range but also in their topological structure. It is possible to distinguish: * Random networks * Free- scale networks * Small-world networks * Local-world networks (en)
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dcterms:subject	Networks
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Link from a Wikipage to another Wikipage	Paul Erdős Node (networking) Small-world network Social network analysis Alfréd Rényi Barabási–Albert model Networks Watts and Strogatz model Small world network
sameAs	Local World Evolving Network Models Local World Evolving Network Models Local World Evolving Network Models Local World Evolving Network Models
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has abstract	Evolving networks are dynamic networks that change through time. In each period there are new nodes and edges that join the network while the old ones disappear. Such dynamic behaviour is characteristic for most real-world networks, regardless of their range - global or local. However, networks differ not only in their range but also in their topological structure. It is possible to distinguish: * Random networks * Free- scale networks * Small-world networks * Local-world networks One of the main feature which allows to differentiate networks is their evolution process. In random networks points are added and removed from the network in a totally random way (model of Erdős and Rényi). Evolution of free scale networks is based on the preferential attachment – nodes connect to nodes that have already possessed a large number of links. In result hubs (nodes that have the largest number of edges) are created and networks follow power law of distribution (model of Barabási and Albert's). In opposite, in small world networks there are no hubs, and nodes are rather egalitarian and locally grouped in smaller clusters. These kind of networks are described by Watts and Strogatz (WS) model. All aforementioned models assume that newly added points have a global information about the whole network. However, in case of large systems, such knowledge is rather rare. This strongly limits nodes’ possibilities of connection choice. As a result, decisions about links are made rather in a local world than in the whole network. Networks which consider this locality are called local-world networks and were first described by the Li and Chen model (2003). The local world model was extended inter alia by Gardeñes and Moreno (2004), Sen and Zhong, Wen et al. or Xuan et al. (en)
gold:hypernym	Networks
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