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CrowdService: optimizing mobile crowdsourcing and service composition

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dc.contributor.author Peng, Xin
dc.contributor.author Gu, Jingxiao
dc.contributor.author Tan, Tian Huat
dc.contributor.author Yu, Yijun
dc.contributor.author Nuseibeh, Bashar
dc.contributor.author Zhao, Wenyun
dc.date.accessioned 2018-05-18T14:47:46Z
dc.date.available 2018-05-18T14:47:46Z
dc.date.issued 2018
dc.identifier.uri http://hdl.handle.net/10344/6852
dc.description peer-reviewed en_US
dc.description.abstract Some user needs can only be met by leveraging the capabilities of others to undertake particular tasks that require intelligence and labor. Crowdsourcing such capabilities is one way to achieve this. But providing a service that leverages crowd intelligence and labor is a challenge, since various factors need to be considered to enable reliable service provisioning. For example, the selection of an optimal set of workers from those who bid to perform a task needs to be made based on their reliability, expected reward, and distance to the target locations. Moreover, for an application involving multiple services, the overall cost and time constraints must be optimally allocated to each involved service. In this paper, we develop a framework, named CROWDSERVICE, which supplies crowd intelligence and labor as publicly accessible crowd services via mobile crowdsourcing. The paper extends our earlier work by providing an approach for constraints synthesis and worker selection. It employs a genetic algorithm to dynamically synthesize and update near-optimal cost and time constraints for each crowd service involved in a composite service, and selects a near-optimal set of workers for each crowd service to be executed. We implement the proposed framework on Android platforms, and evaluate its effectiveness, scalability and usability in both experimental and user studies. en_US
dc.language.iso eng en_US
dc.publisher Association for Computing Machinery en_US
dc.relation ASAP en_US
dc.relation.ispartofseries ACM Transactions on Internet Technology (TOIT) - Special Issue on Internetware and Devops and Regular Papers;18 (2), article 19
dc.relation.uri http://dx.doi.org/10.1145/3108935
dc.rights © ACM, 2018. 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 inACM Transactions on Internet Technology (TOIT) - Special Issue on Internetware and Devops and Regular Papers, 2018, 18 (2), article 2, http://dx.doi.org/10.1145/3108935 en_US
dc.subject CCS concepts en_US
dc.subject information systems en_US
dc.subject crowdsourcing en_US
dc.subject collaborative and social computing systems and tools en_US
dc.subject human-centered computing en_US
dc.title CrowdService: optimizing mobile crowdsourcing and service composition en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1145/3108935
dc.contributor.sponsor National High Technology Development 863 Program of China en_US
dc.contributor.sponsor SFI en_US
dc.contributor.sponsor ERC en_US
dc.relation.projectid 2015AA01A203 en_US
dc.relation.projectid 13/RC/2094 en_US
dc.relation.projectid 291652 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US


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