Understanding mobility in networks: A node embedding approach

TL;DR

This paper introduces a node embedding methodology to analyze and model node mobility in networks, capturing spatial and temporal dynamics better than traditional topological measures.

Contribution

It presents a novel node embedding approach that generalizes node importance over time, improving mobility and connectivity analysis in mobile networks.

Findings

Provides a rich representation of mobility patterns

Unveils spatial and temporal characteristics of nodes

Enhances analysis of node importance over time

Abstract

Motivated by the growing number of mobile devices capable of connecting and exchanging messages, we propose a methodology aiming to model and analyze node mobility in networks. We note that many existing solutions in the literature rely on topological measurements calculated directly on the graph of node contacts, aiming to capture the notion of the node's importance in terms of connectivity and mobility patterns beneficial for prototyping, design, and deployment of mobile networks. However, each measure has its specificity and fails to generalize the node importance notions that ultimately change over time. Unlike previous approaches, our methodology is based on a node embedding method that models and unveils the nodes' importance in mobility and connectivity patterns while preserving their spatial and temporal characteristics. We focus on a case study based on a trace of group meetings. The results show that our methodology provides a rich representation for extracting different mobility and connectivity patterns, which can be helpful for various applications and services in mobile networks.