Plausible Mobility: Inferring Movement from Contacts

TL;DR

This paper presents a heuristic algorithm that infers plausible node mobility from contact traces, enabling richer protocol simulations without complex measurements, by leveraging contact data and anticipation forces.

Contribution

The authors introduce a fast, force-based heuristic algorithm to infer realistic mobility from contact traces, bridging the gap between simple contact data and detailed mobility models.

Findings

The quality of inferred mobility depends on contact trace precision.

Adding anticipation forces improves mobility inference accuracy.

The method works on both synthetic and real contact traces.

Abstract

We address the difficult question of inferring plausible node mobility based only on information from wireless contact traces. Working with mobility information allows richer protocol simulations, particularly in dense networks, but requires complex set-ups to measure, whereas contact information is easier to measure but only allows for simplistic simulation models. In a contact trace a lot of node movement information is irretrievably lost so the original positions and velocities are in general out of reach. We propose a fast heuristic algorithm, inspired by dynamic force-based graph drawing, capable of inferring a plausible movement from any contact trace, and evaluate it on both synthetic and real-life contact traces. Our results reveal that (i) the quality of the inferred mobility is directly linked to the precision of the measured contact trace, and (ii) the simple addition of appropriate anticipation forces between nodes leads to an accurate inferred mobility.