article

Energy-efficient opportunistic coverage for people-centric urban sensing

Authors:

Liang LiuAuthors Info & Claims

Wireless Networks, Volume 20, Issue 6

Pages 1461 - 1476

https://doi.org/10.1007/s11276-014-0687-0

Published: 01 August 2014 Publication History

Abstract

Human-carried or vehicle-mounted sensors can be exploited to collect data ubiquitously for urban sensing. In this work, we study a new coverage problem, opportunistic coverage, to characterize the sensing quality of such people-centric sensing systems. Compared with the traditional static coverage and dynamic coverage in sensor networks, opportunistic coverage has some unique characteristics caused by the requirements of urban sensing applications and human mobility features such as spatio-temporal correlation, hotspots effects and randomness. In order to achieve good trade-off between energy consumption and coverage quality, we propose an offline node selection mechanism and an online adaptive sampling mechanism. The former can select the minimum number of nodes to achieve coverage requirements, based on the history trajectories of the given set of nodes, and the latter can help each selected node to decide whether to perform the sampling task at some time adaptively. Based on a real human mobility dataset and a taxi mobility dataset, extensive simulation results evaluate that our proposed models and mechanisms are effective and efficient in terms of energy consumption and coverage quality.

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Cited By

Wang LYu ZZhang DGuo BLiu C(2018)Heterogeneous Multi-Task Assignment in Mobile Crowdsensing Using Spatiotemporal CorrelationIEEE Transactions on Mobile Computing10.1109/TMC.2018.282737518:1(84-97)Online publication date: 3-Dec-2018
https://dl.acm.org/doi/10.1109/TMC.2018.2827375
Zhao DMa HLi QTang S(2018)A unified delay analysis framework for opportunistic data collectionWireless Networks10.1007/s11276-016-1403-z24:4(1313-1325)Online publication date: 1-May-2018
https://dl.acm.org/doi/10.1007/s11276-016-1403-z
Corrente G(2017)Performance issues in content dissemination to metropolitan mobile usersJournal of High Speed Networks10.3233/JHS-17056223:2(149-162)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.3233/JHS-170562
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cover image Wireless Networks

Wireless Networks Volume 20, Issue 6

August 2014

416 pages

ISSN:1022-0038

Issue’s Table of Contents

Copyright © Copyright © 2014 Springer Science+Business Media New York.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 August 2014

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Cited By

Wang LYu ZZhang DGuo BLiu C(2018)Heterogeneous Multi-Task Assignment in Mobile Crowdsensing Using Spatiotemporal CorrelationIEEE Transactions on Mobile Computing10.1109/TMC.2018.282737518:1(84-97)Online publication date: 3-Dec-2018
https://dl.acm.org/doi/10.1109/TMC.2018.2827375
Zhao DMa HLi QTang S(2018)A unified delay analysis framework for opportunistic data collectionWireless Networks10.1007/s11276-016-1403-z24:4(1313-1325)Online publication date: 1-May-2018
https://dl.acm.org/doi/10.1007/s11276-016-1403-z
Corrente G(2017)Performance issues in content dissemination to metropolitan mobile usersJournal of High Speed Networks10.3233/JHS-17056223:2(149-162)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.3233/JHS-170562
Chen YLv PGuo DZhou TXu M(2017)Trajectory segment selection with limited budget in mobile crowd sensingPervasive and Mobile Computing10.1016/j.pmcj.2017.06.01040:C(123-138)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1016/j.pmcj.2017.06.010
Wu HMa HLiu LMa HYuan P(2017)A traffic-camera assisted cache-and-relay routing for live video stream delivery in vehicular ad hoc networksWireless Networks10.1007/s11276-016-1272-523:7(2051-2067)Online publication date: 1-Oct-2017
https://dl.acm.org/doi/10.1007/s11276-016-1272-5
Ding SHe XWang JQiao BGai K(2017)Static Node Center Opportunistic Coverage and Hexagonal Deployment in Hybrid Crowd SensingJournal of Signal Processing Systems10.1007/s11265-016-1120-y86:2-3(251-267)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1007/s11265-016-1120-y
Leppänen TÁlvarez Lacasia JTobe YSezaki KRiekki J(2017)Mobile crowdsensing with mobile agentsAutonomous Agents and Multi-Agent Systems10.1007/s10458-015-9311-731:1(1-35)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1007/s10458-015-9311-7
Wang YLi HLi T(2017)Participant selection for data collection through device-to-device communications in mobile sensingPersonal and Ubiquitous Computing10.1007/s00779-016-0974-021:1(31-41)Online publication date: 1-Feb-2017
https://dl.acm.org/doi/10.1007/s00779-016-0974-0
Bradai SKhemakhem SJmaiel M(2016)Web Services Description and Discovery for Mobile CrowdsensingInternational Journal of Information System Modeling and Design10.4018/IJISMD.20161001037:4(31-49)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.4018/IJISMD.2016100103
Wennerström HRohner CBoldrini Cde Amorim M(2016)Towards even coverage monitoring with opportunistic sensor networksProceedings of the Eleventh ACM Workshop on Challenged Networks10.1145/2979683.2979691(81-86)Online publication date: 3-Oct-2016
https://dl.acm.org/doi/10.1145/2979683.2979691
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