Incremental Deployment of Network Monitors Based on Group Betweenness Centrality

TL;DR

This paper introduces a new method for optimally deploying additional network monitors in evolving networks using Group Betweenness Centrality, achieving near-optimal coverage of traffic flow.

Contribution

It presents a novel approach leveraging Group Betweenness Centrality to identify optimal locations for additional monitors in dynamic networks.

Findings

Method achieves at least (1-1/e) of optimal traffic coverage.

Effective for incremental deployment in evolving networks.

Provides a scalable solution for network monitoring expansion.

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.