From Encounters to Plausible Mobility

TL;DR

This paper introduces a fast heuristic algorithm inspired by force-based graph drawing to infer plausible node mobility from contact traces, enhancing simulation accuracy in dense wireless networks.

Contribution

The paper presents a novel, efficient heuristic method to reconstruct plausible mobility patterns solely from contact trace data, improving simulation fidelity.

Findings

Inferred mobility quality depends on contact trace precision.

Adding anticipation forces improves mobility inference accuracy.

The method performs well on both synthetic and real contact traces.

Abstract

Inferring plausible node mobility based only on information from wireless contact traces is a difficult problem. Working with mobility information allows richer protocol simulations, particularly in dense networks, but requires complex set-ups to measure. On the other hand, 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. In this paper, 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.