research-article

Joint bluetooth/wifi scanning framework for characterizing and leveraging people movement in university campus

Authors:

Klara Nahrstedt,

Indranil GuptaAuthors Info & Claims

MSWIM '10: Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems

Pages 257 - 265

https://doi.org/10.1145/1868521.1868563

Published: 17 October 2010 Publication History

Abstract

This paper¹ presents a novel framework called UIM², which collects both location information and ad hoc contacts of the human movement at the University of Illinois campus using Google Android phones. Each UIM experiment phone encompasses a Bluetooth scanner and a wifi scanner capturing both Bluetooth MAC addresses and wifi access point MAC addresses in proximity of the phone. Then, Bluetooth MAC addresses are used to infer contact information and the wifi MAC addresses are used to infer physical location of the phone. Using the contact and location information, we investigate first the sensitivity analysis on contact duration and inter-contact duration. Then, we characterize the regularity of people movement, visit duration of people at locations, and the popularity of locations. Finally, we present the Hybrid Epidemic data dissemination protocol, which uses both wifi access point and ad hoc contact to expedite the data forwarding. We evaluate Hybrid Epidemic protocol with our collected ad hoc and wifi traces and find that in comparison with Epidemic data dissemination protocol, the Hybrid Epidemic protocol improves data forwarding delay considerably.

References

[1]

Android Development. http://developer.android.com/.

[2]

Skyhook. http://www.skyhookwireless.com.

[3]

Data Mining: Concepts and Techniques, pages 225--276. Morgan Kaufmann Publishers, second edition, 2001.

[4]

M. Balazinska and P. Castro. Characterizing mobility and network usage in a corporate wireless local-area network. In Proceedings of Mobisys, 2003.

Digital Library

[5]

A. Chaintreau, P. Hui, J. Crowcroft, C. Diot, R. Gass, and J. Scott. Impact of human mobility on the design of opportunistic forwarding algorithms. In Proceedings of Infocom, 2006.

[6]

N. Eagle and A. (Sandy). Reality mining: sensing complex social systems. Personal and Ubiquitous Computing. 10:255--268, 2006.

Digital Library

[7]

T. Henderson, D. Kotz, and I. Abyzov. The changing usage of a mature campus-wide wireless network. In Proceedings of Mobicom, 2004.

Digital Library

[8]

W. Hsu, T. Spyropoulos, K. Psounis, and A. Helmy. Modeling time-variant user mobility in wireless mobile networks. In Proceedings of Infocom, 2007.

Digital Library

[9]

P. Hui and A. Chaintreaum and J. Scott and R. Gass and J. Crowcroft and C. Diot. Pocket switched networks and human mobility in conference environments. In Proceedings of the ACM SIGCOMM workshop on Delay-tolerant networking, 2005.

Digital Library

[10]

R. Jain, A. Shivaprasad, D. Lelescu, and X. He. Towards a model of user mobility and registration patterns. ACM SIGMOBILE Mobile Computing and Communications Review. 8:59--62, 2004.

Digital Library

[11]

T. Karagiannis, J.-Y. Le Boudec, and M. Vojnovic. Power law and exponential decay of inter contact times between mobile devices. In Proceedings of Mobicom, 2007.

Digital Library

[12]

J. Krumm and K. Hinckley. The nearme wireless proximity server. In Proceedings of Ubicomp, 2004.

[13]

J.-K. Lee and J. C. Hou. Modeling steady-state and transient behaviors of user mobility: formulation, analysis, and application. In Proceedings of Mobihoc, 2006.

Digital Library

[14]

J. Leguay, A. Lindgren, J. Scott, T. Friedman, and J. Crowcroft. Opportunistic content distribution in an urban setting. In Proceedings of CHANTS, 2006.

Digital Library

[15]

L. McNamara, C. Mascolo, and Licai Capra. Media sharing based on colocation prediction in urban transport. In Proceedings of Mobicom, 2008.

Digital Library

[16]

M. Motani, V. Srinivasan, and P. S. Nuggehalli. PeopleNet: Engineering A wireless Virtual Social Network. In Proceedings of MOBICOM, 2005.

Digital Library

[17]

I. Rhee, M.Shin, S. Hong, K. Lee, S. Kim, and S. Chong. Trace NCSU GPS, 2009.

[18]

E. P. S. Gaito and G. P. Rossi. Opportunistic forwarding in workplaces. In Proceedings of ACM WOSN, 2009.

Digital Library

[19]

T. Small and Z. J. Haas. The shared wireless infostation model: a new ad hoc networking paradigm (or where there is a whale, there is a way). In Proceedings of MOBIHOC, 2003.

Digital Library

[20]

T. Spyropoulos, K. Psounis, and C. S. Raghavendra. Spray and wait: an efficient routing scheme for intermittently connected mobile networks. In Proceedings of the SIGCOMM workshop on Delay-tolerant networking, 2005.

Digital Library

[21]

J. Su, A. Chin, A. Popivanova, A. Goel, and E. de Lara. User mobility for opportunistic ad-hoc networking. In Proceedings of the Sixth IEEE Workshop on Mobile Computing Systems and Applications, 2004.

Digital Library

[22]

P.-U. Tournoux, J. Leguay, F. Benbadis, V. Conan, M. Dias de Amorim, and J. Whitbeck. The accordion phenomenon: analysis, characterization, and impact on dtn routing. In Proceedings of IEEE Infocom, 2010.

[23]

Vahdat, A. and Becker, D. Epidemic routing for partially connected ad hoc networks. In Technical Report CS-200006, Duke University, 2000.

[24]

S. van der Spek. Location Based Services and TeleCartography II (Mapping Pedestrian Movement: Using Tracking Technologies in Koblenz), pages 95--118. Springer Berlin Heidelberg, 2009.

Cited By

Koteich JMitton N(2024)Dataset Collection of Multi-Communication Technologies Monitored in Different Mobility Contexts2024 International Wireless Communications and Mobile Computing (IWCMC)10.1109/IWCMC61514.2024.10592486(0439-0444)Online publication date: 27-May-2024
https://doi.org/10.1109/IWCMC61514.2024.10592486
Mokryn OAbbey AMarmor YShahar Y(2024)Evaluating the dynamic interplay of social distancing policies regarding airborne pathogens through a temporal interaction-driven model that uses real-world and synthetic dataJournal of Biomedical Informatics10.1016/j.jbi.2024.104601151(104601)Online publication date: Mar-2024
https://doi.org/10.1016/j.jbi.2024.104601
Génois MZens MOliveira MLechner CSchaible JStrohmaier M(2023)Combining Sensors and Surveys to Study Social Interactions: A Case of Four Science ConferencesPersonality Science10.5964/ps.99574:1Online publication date: 7-Jun-2023
https://doi.org/10.5964/ps.9957
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Index Terms

Joint bluetooth/wifi scanning framework for characterizing and leveraging people movement in university campus
1. Hardware
  1. Communication hardware, interfaces and storage
2. Networks

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cover image ACM Conferences

MSWIM '10: Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems

October 2010

424 pages

ISBN:9781450302746

DOI:10.1145/1868521

General Chairs:
Violet R. Syrotiuk
Arizona State University, USA
,
Fatih Alagöz
Bogazici University, Turkey
,
Program Chairs:
Brahim Bensaou
The Hong Kong University of Science & Technology, Hong Kong
,
Özgür B. Akan
Koç University, Turkey

Copyright © 2010 ACM.

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 ACM 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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SIGSIM: ACM Special Interest Group on Simulation and Modeling

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Association for Computing Machinery

New York, NY, United States

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Published: 17 October 2010

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MSWiM '10

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SIGSIM

MSWiM '10: The 13th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

October 17 - 21, 2010

Bodrum, Turkey

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Cited By

Koteich JMitton N(2024)Dataset Collection of Multi-Communication Technologies Monitored in Different Mobility Contexts2024 International Wireless Communications and Mobile Computing (IWCMC)10.1109/IWCMC61514.2024.10592486(0439-0444)Online publication date: 27-May-2024
https://doi.org/10.1109/IWCMC61514.2024.10592486
Mokryn OAbbey AMarmor YShahar Y(2024)Evaluating the dynamic interplay of social distancing policies regarding airborne pathogens through a temporal interaction-driven model that uses real-world and synthetic dataJournal of Biomedical Informatics10.1016/j.jbi.2024.104601151(104601)Online publication date: Mar-2024
https://doi.org/10.1016/j.jbi.2024.104601
Génois MZens MOliveira MLechner CSchaible JStrohmaier M(2023)Combining Sensors and Surveys to Study Social Interactions: A Case of Four Science ConferencesPersonality Science10.5964/ps.99574:1Online publication date: 7-Jun-2023
https://doi.org/10.5964/ps.9957
Marmor YAbbey AShahar YMokryn O(2023)Assessing individual risk and the latent transmission of COVID-19 in a population with an interaction-driven temporal modelScientific Reports10.1038/s41598-023-39817-913:1Online publication date: 10-Aug-2023
https://doi.org/10.1038/s41598-023-39817-9
Duives Dvan Oijen THoogendoorn S(2020)Enhancing Crowd Monitoring System Functionality through Data Fusion: Estimating Flow Rate from Wi-Fi Traces and Automated Counting System DataSensors10.3390/s2021603220:21(6032)Online publication date: 23-Oct-2020
https://doi.org/10.3390/s20216032
Santana JSanchez LSotres PLanza JLlorente TMunoz L(2020)A Privacy-Aware Crowd Management System for Smart Cities and Smart BuildingsIEEE Access10.1109/ACCESS.2020.30106098(135394-135405)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3010609
Valks BArkesteijn MKoutamanis Aden Heijer A(2020)Towards a smart campus: supporting campus decisions with Internet of Things applicationsBuilding Research & Information10.1080/09613218.2020.178470249:1(1-20)Online publication date: 7-Jul-2020
https://doi.org/10.1080/09613218.2020.1784702
Das Swain VReddy MNies KTay LDe Choudhury MAbowd G(2019)Birds of a Feather Clock TogetherProceedings of the ACM on Human-Computer Interaction10.1145/33592673:CSCW(1-30)Online publication date: 7-Nov-2019
https://dl.acm.org/doi/10.1145/3359267
Lesani AMiranda-Moreno L(2019)Development and Testing of a Real-Time WiFi-Bluetooth System for Pedestrian Network Monitoring, Classification, and Data ExtrapolationIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2018.285489520:4(1484-1496)Online publication date: Apr-2019
https://doi.org/10.1109/TITS.2018.2854895
Andión JNavarro JLópez GÁlvarez-Campana MDueñas JLanza J(2018)Smart Behavioral Analytics over a Low-Cost IoT Wi-Fi Tracking Real DeploymentWireless Communications & Mobile Computing10.1155/2018/31364712018Online publication date: 2-Dec-2018
https://dl.acm.org/doi/10.1155/2018/3136471
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