Heterogeneous Participant Recruitment for Comprehensive Vehicle Sensing

Yazhi Liu and Xiong Li

PLOS ONE, 2015, vol. 10, issue 9, 1-19

Abstract: Widely distributed mobile vehicles wherein various sensing devices and wireless communication interfaces are installed bring vehicular participatory sensing into practice. However, the heterogeneity of vehicles in terms of sensing capability and mobility, and the participants’ expectations on the incentives blackmake the collection of comprehensive sensing data a challenging task. A sensing data quality-oriented optimal heterogeneous participant recruitment strategy is proposed in this paper for vehicular participatory sensing. In the proposed strategy, the differences between the sensing data requirements and the collected sensing data are modeled. An optimization formula is established to model the optimal participant recruitment problem, and a participant utility analysis scheme is built based on the sensing and mobility features of vehicles. Besides, a greedy algorithm is then designed according to the utility of vehicles to recruit the most efficient vehicles with a limited total incentive budget. Real trace-driven simulations show that the proposed strategy can collect 85.4% of available sensing data with 34% incentive budget.

Date: 2015
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0138898 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 38898&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0138898

DOI: 10.1371/journal.pone.0138898

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().