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Article: A Survey of Mobile Crowdsensing Techniques: A Critical Component for The Internet of Things

TitleA Survey of Mobile Crowdsensing Techniques: A Critical Component for The Internet of Things
Authors
KeywordsMobile crowdsensing
redundancy elimination
cost-effectiveness
quality of service
Internet of Things
Issue Date2018
PublisherAssociation for Computing Machinery. The Journal's web site is located at https://tcps.acm.org/
Citation
ACM Transactions on Cyber-Physical Systems, 2018, v. 2 n. 3, p. article no. 18 How to Cite?
AbstractMobile crowdsensing serves as a critical building block for emerging Internet of Things (IoT) applications. However, the sensing devices continuously generate a large amount of data, which consumes much resources (e.g., bandwidth, energy, and storage) and may sacrifice the Quality-of-Service (QoS) of applications. Prior work has demonstrated that there is significant redundancy in the content of the sensed data. By judiciously reducing redundant data, data size and load can be significantly reduced, thereby reducing resource cost and facilitating the timely delivery of unique, probably critical information and enhancing QoS. This article presents a survey of existing works on mobile crowdsensing strategies with an emphasis on reducing resource cost and achieving high QoS. We start by introducing the motivation for this survey and present the necessary background of crowdsensing and IoT. We then present various mobile crowdsensing strategies and discuss their strengths and limitations. Finally, we discuss future research directions for mobile crowdsensing for IoT. The survey addresses a broad range of techniques, methods, models, systems, and applications related to mobile crowdsensing and IoT. Our goal is not only to analyze and compare the strategies proposed in prior works, but also to discuss their applicability toward the IoT and provide guidance on future research directions for mobile crowdsensing.
DescriptionSpecial Issue on the Internet of Things: Part 2
Persistent Identifierhttp://hdl.handle.net/10722/278767
ISSN
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLiu, J-
dc.contributor.authorShen, H-
dc.contributor.authorNarman, HS-
dc.contributor.authorChung, W-
dc.contributor.authorLin, Z-
dc.date.accessioned2019-10-21T02:13:42Z-
dc.date.available2019-10-21T02:13:42Z-
dc.date.issued2018-
dc.identifier.citationACM Transactions on Cyber-Physical Systems, 2018, v. 2 n. 3, p. article no. 18-
dc.identifier.issn2378-962X-
dc.identifier.urihttp://hdl.handle.net/10722/278767-
dc.descriptionSpecial Issue on the Internet of Things: Part 2-
dc.description.abstractMobile crowdsensing serves as a critical building block for emerging Internet of Things (IoT) applications. However, the sensing devices continuously generate a large amount of data, which consumes much resources (e.g., bandwidth, energy, and storage) and may sacrifice the Quality-of-Service (QoS) of applications. Prior work has demonstrated that there is significant redundancy in the content of the sensed data. By judiciously reducing redundant data, data size and load can be significantly reduced, thereby reducing resource cost and facilitating the timely delivery of unique, probably critical information and enhancing QoS. This article presents a survey of existing works on mobile crowdsensing strategies with an emphasis on reducing resource cost and achieving high QoS. We start by introducing the motivation for this survey and present the necessary background of crowdsensing and IoT. We then present various mobile crowdsensing strategies and discuss their strengths and limitations. Finally, we discuss future research directions for mobile crowdsensing for IoT. The survey addresses a broad range of techniques, methods, models, systems, and applications related to mobile crowdsensing and IoT. Our goal is not only to analyze and compare the strategies proposed in prior works, but also to discuss their applicability toward the IoT and provide guidance on future research directions for mobile crowdsensing.-
dc.languageeng-
dc.publisherAssociation for Computing Machinery. The Journal's web site is located at https://tcps.acm.org/-
dc.relation.ispartofACM Transactions on Cyber-Physical Systems-
dc.rightsACM Transactions on Cyber-Physical Systems. Copyright © Association for Computing Machinery.-
dc.rights©ACM, YYYY. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in PUBLICATION, {VOL#, ISS#, (DATE)} http://doi.acm.org/10.1145/nnnnnn.nnnnnn-
dc.subjectMobile crowdsensing-
dc.subjectredundancy elimination-
dc.subjectcost-effectiveness-
dc.subjectquality of service-
dc.subjectInternet of Things-
dc.titleA Survey of Mobile Crowdsensing Techniques: A Critical Component for The Internet of Things-
dc.typeArticle-
dc.identifier.emailChung, W: wchun@hku.hk-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1145/3185504-
dc.identifier.scopuseid_2-s2.0-85084305844-
dc.identifier.hkuros307642-
dc.identifier.volume2-
dc.identifier.issue3-
dc.identifier.spagearticle no. 18-
dc.identifier.epagearticle no. 18-
dc.identifier.isiWOS:000458603800004-
dc.publisher.placeUnited States-

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