Estimating the degree centrality ranking

dc.contributor.author	Saxena, A.
dc.contributor.author	Malik, V.
dc.contributor.author	Iyengar, S.R.S
dc.date.accessioned	2016-11-18T11:42:17Z
dc.date.available	2016-11-18T11:42:17Z
dc.date.issued	2016-11-18
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/458
dc.description.abstract	Complex networks have gained more attention from the last few years. The size of the real world complex networks, such as online social networks, WWW networks, collaboration networks, is exponentially increasing with time. It is not feasible to completely collect, store and process these networks. In the present work, we propose a method to estimate degree centrality ranking of a node without having complete structure of the graph. The proposed method uses degree of a node and power law exponent of the degree distribution to calculate the ranking. We also study simulation results on Barabasi-Albert model. Simulation results show that average error in the calculated ranking is approximately 5% of total number of nodes.	en_US
dc.language.iso	en_US	en_US
dc.subject	Social networking (online)	en_US
dc.subject	Average errors	en_US
dc.subject	Barabasi-Albert model	en_US
dc.subject	Collaboration network	en_US
dc.subject	Degree centrality	en_US
dc.subject	Degree distributions	en_US
dc.subject	Degree of a nodes	en_US
dc.subject	On-line social networks	en_US
dc.subject	Power law exponent	en_US
dc.subject	Complex networks	en_US
dc.title	Estimating the degree centrality ranking	en_US
dc.type	Article	en_US