Mobile Crowd Sensing (MCS) is the special case of crowdsourcing, which leverages the smartphones with various embedded sensors and user's mobility to sense diverse phenomenon in a city. Task allocation is a fundamental research issue in MCS, which is crucial for the efficiency and effectiveness of MCS applications. In this article, we specifically focus on the task allocation in MCS systems. We first present the unique features of MCS allocation compared to generic crowdsourcing, and then provide a comprehensive review for diversifying problem formulation and allocation algorithms together with future research opportunities.
@article{arxiv.1805.08418,
title = {Task Allocation in Mobile Crowd Sensing: State of the Art and Future Opportunities},
author = {Jiangtao Wang and Leye Wang and Yasha Wang and Daqing Zhang and Linghe Kong},
journal= {arXiv preprint arXiv:1805.08418},
year = {2018}
}