Using Location-Based Social Networks to Validate Human Mobility and Relationships Models

TL;DR

This paper leverages location-based social network data to validate and improve human mobility and relationship models, aiming to enhance the realism of simulations in mobile ad-hoc and delay tolerant networks.

Contribution

It introduces a methodology to use social networking data for validating and refining mobility and relationship models, moving beyond traditional random models.

Findings

Human movements show repeated patterns and are distance-bound.

Social relationships correlate with physical proximity.

Validated models better reflect real human mobility and social interactions.

Abstract

We propose to use social networking data to validate mobility models for pervasive mobile ad-hoc networks (MANETs) and delay tolerant networks (DTNs). The Random Waypoint (RWP) and Erdos-Renyi (ER) models have been a popular choice among researchers for generating mobility traces of nodes and relationships between them. Not only RWP and ER are useful in evaluating networking protocols in a simulation environment, but they are also used for theoretical analysis of such dynamic networks. However, it has been observed that neither relationships among people nor their movements are random. Instead, human movements frequently contain repeated patterns and friendship is bounded by distance. We used social networking site Gowalla to collect, create and validate models of human mobility and relationships for analysis and evaluations of applications in opportunistic networks such as sensor networks and transportation models in civil engineering. In doing so, we hope to provide more human-like movements and social relationship models to researchers to study problems in complex and mobile networks.