Share the Crowdsensing Data with Local Crowd by V2V Communications

Joint Authors

Dai, Xili
Song, Chao
Liu, Ming

Source

Mobile Information Systems

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-14, 14 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-04-24

Country of Publication

Egypt

No. of Pages

14

Main Subjects

Telecommunications Engineering

Abstract EN

With an increase in the number of mobile applications, the development of mobile crowdsensing systems has recently attracted significant attention from both academic researchers and industries.

In mobile crowdsensing system, the remote cloud (or back-end server) harvests all the crowdsensing data from the mobile devices, and the crowdsensing data can be uploaded immediately via 3G/4G.

To reduce the cost and energy consumption, many academic researchers and industries investigate the way of mobile data offloading.

Due to the sparse distribution of the WiFi APs, offloading the crowdsensing data is often delayed.

In this paper, compared with offloading data via WiFi APs, we investigate the communication and sharing of crowdsensing data by vehicles near the event (such as a pothole on the road), termed as a local crowd.

In such crowd, a vehicle can transmit the data to each other by vehicle-to-vehicle (V2V) communication.

The crowd-based approach has a lower delay than the offloading-based approach, by considering the quality of truth discovery.

We define a utility function related to the crowdsensing data shared by the local crowd in order to quantify the trade-off between the quality of the truth discovery and the user satisfaction.

Our extensional simulations verify the effectiveness of our proposed schemes.

American Psychological Association (APA)

Song, Chao& Liu, Ming& Dai, Xili. 2016. Share the Crowdsensing Data with Local Crowd by V2V Communications. Mobile Information Systems،Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1111565

Modern Language Association (MLA)

Song, Chao…[et al.]. Share the Crowdsensing Data with Local Crowd by V2V Communications. Mobile Information Systems No. 2016 (2016), pp.1-14.
https://search.emarefa.net/detail/BIM-1111565

American Medical Association (AMA)

Song, Chao& Liu, Ming& Dai, Xili. Share the Crowdsensing Data with Local Crowd by V2V Communications. Mobile Information Systems. 2016. Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1111565

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1111565