Design and evaluation of characteristic incentive mechanisms in Mobile Crowdsensing Systems
- Submitting institution
-
Bournemouth University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 212121
- Type
- D - Journal article
- DOI
-
10.1016/j.simpat.2015.04.007
- Title of journal
- Simulation Modelling Practice and Theory
- Article number
- 0
- First page
- 95
- Volume
- 55
- Issue
- 0
- ISSN
- 1569-190X
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2015
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
-
- Research group(s)
-
-
- Citation count
- 6
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work was the first in the literature to identify sensing tasks for Mobile Crowdsensing Systems of varying monotonicity in terms of their utility function. This was in contrast to the state of the art that assumed that the more sampling points (i.e. individual Crowd members) an MCS would engage, the higher the utility the system would enjoy; subsequent lines of research took this into consideration. Furthermore, the identified basic MCS components are reflected on the reference model specified in ITU-T Recommendation Y.4205 “Requirements and reference model of IoT-related crowdsourced systems” published later in February 2019.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -