Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

New measures for characterizing the significance of nodes in wireless ad hoc networks via localized path-based neighborhood analysis

New measures for characterizing the significance of nodes in wireless ad hoc networks via... The synergy between social network analysis and wireless ad hoc network protocol design has recently created increased interest for developing methods and measures that capture the topological characteristics of a wireless network. Such techniques are used for the design of routing and multicasting protocols, for cooperative caching purposes and so on. These techniques are mandatory to characterize the network topology using only limited, local connectivity information—one or two hop information. Even though it seems that such techniques can straightforwardly be derived from the respective network-wide techniques, their design presents significant challenges since they must capture rich information using limited knowledge. This article examines the issue of finding the most central nodes in neighborhoods of a given network with directed or undirected links taking into account only localized connectivity information. An algorithm that calculates the ranking, taking into account the N-hop neighborhood of each node is proposed. The method is compared to popular existing schemes for ranking, using Spearman’s rank correlation coefficient. An extended, faster algorithm which reduces the size of the examined network is also described. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Social Network Analysis and Mining Springer Journals

New measures for characterizing the significance of nodes in wireless ad hoc networks via localized path-based neighborhood analysis

Loading next page...
 
/lp/springer-journals/new-measures-for-characterizing-the-significance-of-nodes-in-wireless-R6fvk2FTPv
Publisher
Springer Journals
Copyright
Copyright © 2011 by Springer-Verlag
Subject
Computer Science; Data Mining and Knowledge Discovery; Applications of Graph Theory and Complex Networks; Game Theory, Economics, Social and Behav. Sciences; Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law; Methodology of the Social Sciences
ISSN
1869-5450
eISSN
1869-5469
DOI
10.1007/s13278-011-0029-5
Publisher site
See Article on Publisher Site

Abstract

The synergy between social network analysis and wireless ad hoc network protocol design has recently created increased interest for developing methods and measures that capture the topological characteristics of a wireless network. Such techniques are used for the design of routing and multicasting protocols, for cooperative caching purposes and so on. These techniques are mandatory to characterize the network topology using only limited, local connectivity information—one or two hop information. Even though it seems that such techniques can straightforwardly be derived from the respective network-wide techniques, their design presents significant challenges since they must capture rich information using limited knowledge. This article examines the issue of finding the most central nodes in neighborhoods of a given network with directed or undirected links taking into account only localized connectivity information. An algorithm that calculates the ranking, taking into account the N-hop neighborhood of each node is proposed. The method is compared to popular existing schemes for ranking, using Spearman’s rank correlation coefficient. An extended, faster algorithm which reduces the size of the examined network is also described.

Journal

Social Network Analysis and MiningSpringer Journals

Published: Jun 30, 2011

References