Reverse Engineering Human Mobility in Large-scale Natural Disasters
Abstract
Delay/Disruption-Tolerant Networks (DTNs) have been around for more than a decade and have especially been proposed to be used in scenarios where communication infrastructure is unavailable. In such scenarios, DTNs can offer a best-effort communication service by exploiting user mobility. Natural disasters are an important application scenario for DTNs when the cellular network is destroyed by natural forces. To assess the performance of such networks before deployment, we require appropriate knowledge of human mobility. In this paper, we address this problem by designing, implementing, and evaluating a novel mobility model for large-scale natural disasters. Due to the lack of GPS traces, we reverse-engineer human mobility of past natural disasters (focusing on 2010 Haiti earthquake and 2013 Typhoon Haiyan) by leveraging knowledge of 126 experts from 71 Disaster Response Organizations (DROs). By means of simulation-based experiments, we compare and contrast our mobility model to other well-known models, and evaluate their impact on DTN performance. Finally, we make our source code available to the public.
Keywords
Cite
@article{arxiv.1708.02151,
title = {Reverse Engineering Human Mobility in Large-scale Natural Disasters},
author = {Milan Stute and Max Maass and Tom Schons and Matthias Hollick},
journal= {arXiv preprint arXiv:1708.02151},
year = {2017}
}
Comments
To appear in Proceedings of MSWiM '17. 8 Pages, 9 Figures. Source code and data available at https://github.com/seemoo-lab/natural-disaster-mobility