Quick Detection of Nodes with Large Degrees

Our goal is to quickly find top \(k\) lists of nodes with the largest degrees in large complex networks. If the adjacency list of the network is known (not often the case in complex networks), a deterministic algorithm to find a node with the largest degree requires an average complexity of O(n), wh...

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Bibliographic Details
Published inarXiv.org
Main Authors Avrachenkov, Konstantin, Litvak, Nelly, Sokol, Marina, Towsley, Don
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 15.02.2012
Subjects
Algorithms
Complexity
Networks
Nodes
Random walk
Random walk theory
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Summary:Our goal is to quickly find top \(k\) lists of nodes with the largest degrees in large complex networks. If the adjacency list of the network is known (not often the case in complex networks), a deterministic algorithm to find a node with the largest degree requires an average complexity of O(n), where \(n\) is the number of nodes in the network. Even this modest complexity can be very high for large complex networks. We propose to use the random walk based method. We show theoretically and by numerical experiments that for large networks the random walk method finds good quality top lists of nodes with high probability and with computational savings of orders of magnitude. We also propose stopping criteria for the random walk method which requires very little knowledge about the structure of the network.
ISSN:2331-8422