Article

On profiling mobility and predicting locations of wireless users

Authors:

Matthew J. Beal,

Chunming QiaoAuthors Info & Claims

REALMAN '06: Proceedings of the 2nd international workshop on Multi-hop ad hoc networks: from theory to reality

Pages 55 - 62

https://doi.org/10.1145/1132983.1132993

Published: 26 May 2006 Publication History

Abstract

In this paper, we analyze a year long wireless network users' mobility trace data collected on ETH Zurich campus. Unlike earlier work in [4,18], we profile the movement pattern of wireless users and predict their locations. More specifically, we show that each network user regularly visits a list of places such as a building (also referred to as "hubs") with some probability. The daily list of hubs, along with their corresponding visit probabilities, are referred to as a mobility profile. We also show that over a period of time (e.g., a week), a user may repeatedly follow a mixture of mobility profiles with certain probabilities associated with each of the profiles. Our analysis of the mobility trace data not only validate the existence of our so-called sociological orbits [8], but also demonstrate the advantages of exploiting it in performing hub-level location predictions In particular, we show that such profile based location predictions are more precise than common statistical approaches based on observed hub visitation frequencies alone.

References

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Cited By

De Paola AGaglio SGiammanco ALo Re GMorana M(2021)A multi‐agent system for itinerary suggestion in smart environmentsCAAI Transactions on Intelligence Technology10.1049/cit2.120566:4(377-393)Online publication date: 8-Sep-2021
https://doi.org/10.1049/cit2.12056
Guntuka SShakshuki EKaja SYasar A(2020)Queue based Vehicular Ad Hoc Network Prognostic Offloading ApproachProcedia Computer Science10.1016/j.procs.2020.03.129170(584-593)Online publication date: 2020
https://doi.org/10.1016/j.procs.2020.03.129
Shah SKumar S(2018)A Markov Chain Based Link Lifetime Prediction in Mobile Ad Hoc Networks2018 6th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)10.1109/W-FiCloud.2018.00011(28-33)Online publication date: Aug-2018
https://doi.org/10.1109/W-FiCloud.2018.00011
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Index Terms

On profiling mobility and predicting locations of wireless users
1. Hardware
  1. Communication hardware, interfaces and storage
2. Networks

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Published In

cover image ACM Conferences

REALMAN '06: Proceedings of the 2nd international workshop on Multi-hop ad hoc networks: from theory to reality

May 2006

142 pages

ISBN:1595933603

DOI:10.1145/1132983

General Chair:
Marco Conti
IIT-CNR, Italy
,
Program Chairs:
Jon Crowcroft
University of Cambridge, Computer Laboratory, UK
,
Andrea Passarella
IIT-CNR, Italy

Copyright © 2006 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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Publication History

Published: 26 May 2006

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REALMAN06: Multi-hop Ad Hoc Networks: From Theory to Reality Workshop 2006

May 26, 2006

Florence, Italy

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Cited By

De Paola AGaglio SGiammanco ALo Re GMorana M(2021)A multi‐agent system for itinerary suggestion in smart environmentsCAAI Transactions on Intelligence Technology10.1049/cit2.120566:4(377-393)Online publication date: 8-Sep-2021
https://doi.org/10.1049/cit2.12056
Guntuka SShakshuki EKaja SYasar A(2020)Queue based Vehicular Ad Hoc Network Prognostic Offloading ApproachProcedia Computer Science10.1016/j.procs.2020.03.129170(584-593)Online publication date: 2020
https://doi.org/10.1016/j.procs.2020.03.129
Shah SKumar S(2018)A Markov Chain Based Link Lifetime Prediction in Mobile Ad Hoc Networks2018 6th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)10.1109/W-FiCloud.2018.00011(28-33)Online publication date: Aug-2018
https://doi.org/10.1109/W-FiCloud.2018.00011
Cheung MHou FHuang JSouthwell R(2017)Congestion-Aware DNS for Integrated Cellular and Wi-Fi NetworksIEEE Journal on Selected Areas in Communications10.1109/JSAC.2017.268738335:6(1269-1281)Online publication date: Jun-2017
https://doi.org/10.1109/JSAC.2017.2687383
Mourchid FKobbane ABen Othman JEl Koutbi M(2017)CGAM: A community and geography aware mobility modelInternational Journal of Communication Systems10.1002/dac.343231:1Online publication date: 27-Sep-2017
https://doi.org/10.1002/dac.3432
Pang CJiang YLi Q(2016)FADE: Detecting forwarding anomaly in software-defined networks2016 IEEE International Conference on Communications (ICC)10.1109/ICC.2016.7510990(1-6)Online publication date: May-2016
https://doi.org/10.1109/ICC.2016.7510990
Pang HWang PGao LTang MHuang JSun L(2016)Crowdsourced mobility prediction based on spatio-temporal contexts2016 IEEE International Conference on Communications (ICC)10.1109/ICC.2016.7510707(1-6)Online publication date: May-2016
https://doi.org/10.1109/ICC.2016.7510707
Yan CWang PPang HSun LYang S(2016)CELoF: WiFi Dwell Time Estimation in Free EnvironmentMultiMedia Modeling10.1007/978-3-319-51811-4_41(503-514)Online publication date: 31-Dec-2016
https://doi.org/10.1007/978-3-319-51811-4_41
Ahlers DAulie KEriksen JKrogstie J(2016)Visualizing a City Within a City – Mapping Mobility Within a University CampusSmart City 360°10.1007/978-3-319-33681-7_41(492-503)Online publication date: 29-Jun-2016
https://doi.org/10.1007/978-3-319-33681-7_41
Nielsen JMadsen TSchwefel H(2015)On the benefits of location-based relay selection in mobile wireless networksAnnals of Telecommunications10.1007/s12243-015-0491-671:5-6(211-222)Online publication date: 21-Dec-2015
https://doi.org/10.1007/s12243-015-0491-6
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