Several novel metrics have been proposed in recent literature in order to study the relative importance of nodes in complex networks. Among those, k-coreness has found a number of applications in areas as diverse as sociology, proteinomics, graph visualization, and distributed system analysis and design. This paper proposes new distributed algorithms for the computation of the k-coreness of a network, a process also known as k-core decomposition. This technique 1) allows the decomposition, over a set of connected machines, of very large graphs, when size does not allow storing and processing them on a single host, and 2) enables the runtime computation of k-cores in "live" distributed systems. Lower bounds on the algorithms complexity are given, and an exhaustive experimental analysis on real-world data sets is provided. © 2012 IEEE.

Distributed k-Core Decomposition

Montresor, Alberto;
2013-01-01

Abstract

Several novel metrics have been proposed in recent literature in order to study the relative importance of nodes in complex networks. Among those, k-coreness has found a number of applications in areas as diverse as sociology, proteinomics, graph visualization, and distributed system analysis and design. This paper proposes new distributed algorithms for the computation of the k-coreness of a network, a process also known as k-core decomposition. This technique 1) allows the decomposition, over a set of connected machines, of very large graphs, when size does not allow storing and processing them on a single host, and 2) enables the runtime computation of k-cores in "live" distributed systems. Lower bounds on the algorithms complexity are given, and an exhaustive experimental analysis on real-world data sets is provided. © 2012 IEEE.
2013
2
Montresor, Alberto; F. D., Pellegrini; D., Miorandi
File in questo prodotto:
File Dimensione Formato  
k-core.pdf

Solo gestori archivio

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 3.22 MB
Formato Adobe PDF
3.22 MB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/95535
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 166
  • ???jsp.display-item.citation.isi??? 128
  • OpenAlex ND
social impact