Identifying roles in an IP network with temporal and structural density

TL;DR

This paper introduces a new density measure for IP traffic that considers both temporal and structural aspects, aiding in identifying roles and differences within network activities.

Contribution

It proposes a generalized density concept that extends clustering coefficient, enabling better analysis of IP traffic roles and activity patterns.

Findings

Distinguishes different traffic segments based on density features

Identifies key nodes and groups with specific roles in the network

Reveals structural and temporal differences in network interactions

Abstract

Captures of IP traffic contain much information on very different kinds of activities like file transfers, users interacting with remote systems, automatic backups, or distributed computations. Identifying such activities is crucial for an appropriate analysis, modeling and monitoring of the traffic. We propose here a notion of density that captures both temporal and structural features of interactions, and generalizes the classical notion of clustering coefficient. We use it to point out important differences between distinct parts of the traffic, and to identify interesting nodes and groups of nodes in terms of roles in the network.