research-article

Understanding Opportunistic Networking for Emergency Services: Analysis of One Year of GPS Traces

Authors:

Sergio Cabrero,

Roberto García,

Xabiel G. Pañeda,

David MelendiAuthors Info & Claims

CHANTS '15: Proceedings of the 10th ACM MobiCom Workshop on Challenged Networks

Pages 31 - 36

https://doi.org/10.1145/2799371.2799381

Published: 11 September 2015 Publication History

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Abstract

Opportunistic networking can help emergency services in both their daily operation and disaster relief. This idea has been extensively explored in previous research, but most studies are based on little knowledge of real mobility. In order to support future research, this paper analyses one year of GPS traces from a fire department. The results reveal the characteristics of hypothetic opportunistic networks formed by devices following this mobility considering different communication ranges. We found that the networks analysed are heterogeneous in many dimensions. They are also sparse and partitioned, but delay-tolerant routes connecting these partitions exist. To ease the discovery of these routes, we reveal in the connections between nodes. These findings can be applied in the design and deployment of solutions from the physical to the application layer.

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Cited By

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Gandhi JNarmawala Z(2024)A comprehensive survey on Machine Learning techniques in opportunistic networks: Advances, challenges and future directionsPervasive and Mobile Computing10.1016/j.pmcj.2024.101917100(101917)Online publication date: May-2024
https://doi.org/10.1016/j.pmcj.2024.101917
Musznicki BPiechowiak MZwierzykowski P(2022)Modeling Real-Life Urban Sensor Networks Based on Open DataSensors10.3390/s2223926422:23(9264)Online publication date: 28-Nov-2022
https://doi.org/10.3390/s22239264
Kaisar S(2021)Emergency Response and Post-Disaster Recovery Using Smartphone-Based ApplicationsDigital Services in Crisis, Disaster, and Emergency Situations10.4018/978-1-7998-6705-0.ch002(31-49)Online publication date: 29-Jan-2021
https://doi.org/10.4018/978-1-7998-6705-0.ch002
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Index Terms

Understanding Opportunistic Networking for Emergency Services: Analysis of One Year of GPS Traces
1. Information systems
  1. Information systems applications

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Information

Published In

CHANTS '15: Proceedings of the 10th ACM MobiCom Workshop on Challenged Networks

September 2015

74 pages

ISBN:9781450335430

DOI:10.1145/2799371

Program Chairs:
Katia Obraczka
UC Santa Cruz, USA
,
Karin Anna Hummel
ETH Zurich, Switzerland

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 September 2015

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Conference

MobiCom'15

Sponsor:

SIGMOBILE

MobiCom'15: The 21th Annual International Conference on Mobile Computing and Networking

September 11, 2015

Paris, France

Acceptance Rates

CHANTS '15 Paper Acceptance Rate 7 of 27 submissions, 26%;

Overall Acceptance Rate 61 of 159 submissions, 38%

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Cited By

View all

Gandhi JNarmawala Z(2024)A comprehensive survey on Machine Learning techniques in opportunistic networks: Advances, challenges and future directionsPervasive and Mobile Computing10.1016/j.pmcj.2024.101917100(101917)Online publication date: May-2024
https://doi.org/10.1016/j.pmcj.2024.101917
Musznicki BPiechowiak MZwierzykowski P(2022)Modeling Real-Life Urban Sensor Networks Based on Open DataSensors10.3390/s2223926422:23(9264)Online publication date: 28-Nov-2022
https://doi.org/10.3390/s22239264
Kaisar S(2021)Emergency Response and Post-Disaster Recovery Using Smartphone-Based ApplicationsDigital Services in Crisis, Disaster, and Emergency Situations10.4018/978-1-7998-6705-0.ch002(31-49)Online publication date: 29-Jan-2021
https://doi.org/10.4018/978-1-7998-6705-0.ch002
Luo CYu XLuo WZhang MLong TWang QWang QHuang W(2021)A moving energy-based routing in DTNs with speed heterogeneityJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-020-02874-3Online publication date: 29-Jan-2021
https://doi.org/10.1007/s12652-020-02874-3
Naves RKhalife HJakllari GConan VBeylot A(2019)A Framework for Evaluating Physical-Layer Network Coding Gains in Multi-Hop Wireless NetworksIEEE Transactions on Mobile Computing10.1109/TMC.2018.288342918:12(2725-2739)Online publication date: 1-Dec-2019
https://doi.org/10.1109/TMC.2018.2883429
Wang QYang HWang QHuang WDeng B(2019)A deep learning based data forwarding algorithm in mobile social networksPeer-to-Peer Networking and Applications10.1007/s12083-019-00741-3Online publication date: 30-Mar-2019
https://doi.org/10.1007/s12083-019-00741-3
Álvarez FAlmon LLieser PMeuser TDylla YRicherzhagen BHollick MSteinmetz RFeldmann MHassan M(2018)Conducting a Large-scale Field Test of a Smartphone-based Communication Network for Emergency ResponseProceedings of the 13th Workshop on Challenged Networks10.1145/3264844.3264845(3-10)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1145/3264844.3264845
Cabrero SPaneda XMelendi DGarcia RPlagemann T(2018)Using Firefighter Mobility Traces to Understand Ad-Hoc Networks in WildfiresIEEE Access10.1109/ACCESS.2017.27783476(1331-1341)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2017.2778347
Huynh VRadenkovic M(2017)A novel cross-layer framework for large scale emergency communications2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC)10.1109/IWCMC.2017.7986616(2152-2157)Online publication date: Jun-2017
https://doi.org/10.1109/IWCMC.2017.7986616

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