A Location-Based Incentive Algorithm For Consecutive Crowd Sensing Tasks
Keywords
Graph Set Cover; Location-based Services; Participatory Sensing
Abstract
Crowd Sensing (CS) is a sensing paradigm that takes advantage from the increasing use of mobile smart devices and their capabilities for sensing and computation. In this paper, we present an incentive mechanism for encourage user participation in schemes of sensing that requires consecutive and regular sampling. The proposed mechanism uses a recurrent reverse auction that no only takes into account the sample price, but also the participants location. We show that our mechanism achieves an optimal budget utilization while guarantees area coverage and a sufficient number of participants in every round.
Publication Date
2-1-2016
Publication Title
IEEE Latin America Transactions
Volume
14
Issue
2
Number of Pages
811-817
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/TLA.2016.7437227
Copyright Status
Unknown
Socpus ID
84964336837 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84964336837
STARS Citation
Jaimes, Luis G.; Vergara Laurens, Idalides J.; and Raij, Andrew, "A Location-Based Incentive Algorithm For Consecutive Crowd Sensing Tasks" (2016). Scopus Export 2015-2019. 3627.
https://stars.library.ucf.edu/scopus2015/3627