Incremental deployment of network monitors based on Group Betweenness Centrality

Authors:
Shlomi Dolev;Yuval Elovici;Rami Puzis;Polina Zilberman
Affiliations:
Ben-Gurion University of the Negev, Department of Computer Science, Beer-Sheva, Israel and Deutsche Telekom Laboratories at Ben-Gurion University of the Negev, Beer-Sheva, Israel;Ben-Gurion University of the Negev, Department of Information Systems Engineering, Beer-Sheva, Israel and Deutsche Telekom Laboratories at Ben-Gurion University of the Negev, Beer-Sheva, Israel;Ben-Gurion University of the Negev, Department of Information Systems Engineering, Beer-Sheva, Israel and Deutsche Telekom Laboratories at Ben-Gurion University of the Negev, Beer-Sheva, Israel;Ben-Gurion University of the Negev, Department of Computer Science, Beer-Sheva, Israel and Deutsche Telekom Laboratories at Ben-Gurion University of the Negev, Beer-Sheva, Israel
Venue:
Information Processing Letters
Year:
2009

Citing 5
Cited 2

A threshold of ln n for approximating set cover

Journal of the ACM (JACM)
Traffic matrix estimation: existing techniques and new directions

Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Optimal positioning of active and passive monitoring devices

CoNEXT '05 Proceedings of the 2005 ACM conference on Emerging network experiment and technology
Finding the most prominent group in complex networks

AI Communications - Network Analysis in Natural Sciences and Engineering
Locating network monitors: Complexity, heuristics, and coverage

Computer Communications

Routing betweenness centrality

Journal of the ACM (JACM)
Maximum betweenness centrality: approximability and tractable cases

WALCOM'11 Proceedings of the 5th international conference on WALCOM: algorithms and computation

Quantified Score

Hi-index	0.89

Visualization

Abstract

In many applications we are required to increase the deployment of a distributed monitoring system on an evolving network. In this paper we present a new method for finding candidate locations for additional deployment in the network. This method is based on the Group Betweenness Centrality (GBC) measure that is used to estimate the influence of a group of nodes over the information flow in the network. The new method assists in finding the location of k additional monitors in the evolving network, such that the portion of additional traffic covered is at least (1-1/e) of the optimal.