research-article

Utility-driven data acquisition in participatory sensing

Authors:

Thanasis G. Papaioannou,

Immanuel Trummer,

Karl AbererAuthors Info & Claims

EDBT '13: Proceedings of the 16th International Conference on Extending Database Technology

Pages 251 - 262

https://doi.org/10.1145/2452376.2452407

Published: 18 March 2013 Publication History

Abstract

Participatory sensing (PS) is becoming a popular data acquisition means for interesting emerging applications. However, as data queries from these applications increase, the sustainability of this platform for multiple concurrent applications is at stake. In this paper, we consider the problem of efficient data acquisition in PS when queries of different types come from different applications. We effectively deal with the issues related to resource constraints, user privacy, data reliability, and uncontrolled mobility. We formulate the problem as multi-query optimization and propose efficient heuristics for its effective solution for the various query types and mixes that enable sustainable sensing. Based on simulations with real and artificial data traces, we found that our heuristic algorithms outperform baseline approaches in a multitude of settings considered.

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Cited By

Author MGarcia-Macias JTentori MAguilar L(2022)Using Crowdsensing to Uncover the Emotional and Subjective Well-Being Perceptions of Children in Underserved Urban EnvironmentsProceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022)10.1007/978-3-031-21333-5_86(864-875)Online publication date: 21-Nov-2022
https://doi.org/10.1007/978-3-031-21333-5_86
Nadeem MGoh HHussain MPonnusamy VHussain MKhan M(2021)Internet of Things for Green Building ManagementRole of IoT in Green Energy Systems10.4018/978-1-7998-6709-8.ch007(156-170)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-6709-8.ch007
Arafeh MEl Barachi MMourad ABelqasmi F(2019)A Blockchain based Architecture for the Detection of Fake Sensing in Mobile Crowdsensing2019 4th International Conference on Smart and Sustainable Technologies (SpliTech)10.23919/SpliTech.2019.8783092(1-6)Online publication date: Jun-2019
https://doi.org/10.23919/SpliTech.2019.8783092
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Index Terms

Utility-driven data acquisition in participatory sensing
1. Computer systems organization
  1. Embedded and cyber-physical systems
  2. Real-time systems
2. Information systems
  1. Information retrieval

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Information

Published In

cover image ACM Other conferences

EDBT '13: Proceedings of the 16th International Conference on Extending Database Technology

March 2013

793 pages

ISBN:9781450315975

DOI:10.1145/2452376

General Chair:
Giovanna Guerrini
Università di Genova, Italy
,
Program Chair:
Norman W. Paton
University of Manchester, UK

Copyright © 2013 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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 March 2013

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EDBT/ICDT '13

EDBT/ICDT '13: Joint 2013 EDBT/ICDT Conferences

March 18 - 22, 2013

Genoa, Italy

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Overall Acceptance Rate 7 of 10 submissions, 70%

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Cited By

Author MGarcia-Macias JTentori MAguilar L(2022)Using Crowdsensing to Uncover the Emotional and Subjective Well-Being Perceptions of Children in Underserved Urban EnvironmentsProceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022)10.1007/978-3-031-21333-5_86(864-875)Online publication date: 21-Nov-2022
https://doi.org/10.1007/978-3-031-21333-5_86
Nadeem MGoh HHussain MPonnusamy VHussain MKhan M(2021)Internet of Things for Green Building ManagementRole of IoT in Green Energy Systems10.4018/978-1-7998-6709-8.ch007(156-170)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-6709-8.ch007
Arafeh MEl Barachi MMourad ABelqasmi F(2019)A Blockchain based Architecture for the Detection of Fake Sensing in Mobile Crowdsensing2019 4th International Conference on Smart and Sustainable Technologies (SpliTech)10.23919/SpliTech.2019.8783092(1-6)Online publication date: Jun-2019
https://doi.org/10.23919/SpliTech.2019.8783092
Chattopadhyay RTham C(2019)A Scalable MDP-Based Sensing and Processing Framework for Vehicular Networks2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)10.1109/PERCOMW.2019.8730813(687-692)Online publication date: Mar-2019
https://doi.org/10.1109/PERCOMW.2019.8730813
Ko HPack SLeung V(2019)Coverage-Guaranteed and Energy-Efficient Participant Selection Strategy in Mobile CrowdsensingIEEE Internet of Things Journal10.1109/JIOT.2018.28804636:2(3202-3211)Online publication date: Apr-2019
https://doi.org/10.1109/JIOT.2018.2880463
Siris VFotiou NMertzianis APolyzos G(2019)Smart application-aware IoT data collectionJournal of Reliable Intelligent Environments10.1007/s40860-019-00077-yOnline publication date: 7-Mar-2019
https://doi.org/10.1007/s40860-019-00077-y
Hosseini MAngelopoulos CChai WKundig S(2019)CrowdcloudCluster Computing10.1007/s10586-018-2843-222:2(455-470)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1007/s10586-018-2843-2
Marios Angelopoulos CNikoletseas SRaptis TRolim J(2019)User Incentivization in Mobile Crowdsensing SystemsMission-Oriented Sensor Networks and Systems: Art and Science10.1007/978-3-319-92384-0_8(259-286)Online publication date: 19-Sep-2019
https://doi.org/10.1007/978-3-319-92384-0_8
Niu XWang JYe QZhang Y(2018)A Privacy-Preserving Incentive Mechanism for Participatory Sensing SystemsSecurity and Communication Networks10.1155/2018/25935372018Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1155/2018/2593537
Bajaj GSingh P(2018)Load-Balanced Task Allocation for Improved System Lifetime in Mobile Crowdsensing2018 19th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM.2018.00040(227-232)Online publication date: Jun-2018
https://doi.org/10.1109/MDM.2018.00040
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