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Reverse Engineering Human Mobility in Large-scale Natural Disasters

Stute, Milan ; Maass, Max ; Schons, Tom ; Hollick, Matthias
ed.: Secure Mobile Networking Lab (2018)
Reverse Engineering Human Mobility in Large-scale Natural Disasters.
The 20th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems. Miami, FL (21.11.2017-25.11.2017)
Conference or Workshop Item, Secondary publication, Publisher's Version

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Item Type: Conference or Workshop Item
Type of entry: Secondary publication
Title: Reverse Engineering Human Mobility in Large-scale Natural Disasters
Language: English
Date: 5 November 2018
Place of Publication: Darmstadt
Year of primary publication: 2017
Book Title: Proceedings of MSWiM '17
Event Title: The 20th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems
Event Location: Miami, FL
Event Dates: 21.11.2017-25.11.2017
Edition: 2. updated version
Corresponding Links:
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.

Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-76823
Classification DDC: 000 Generalities, computers, information > 004 Computer science
Divisions: 20 Department of Computer Science > Sichere Mobile Netze
DFG-Graduiertenkollegs > Research Training Group 2050 Privacy and Trust for Mobile Users
Date Deposited: 05 Nov 2018 12:04
Last Modified: 04 Jan 2024 09:54
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/7682
PPN: 438502752
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