# Task Allocation in Mobile Crowd Sensing: State of the Art and Future Opportunities

arXiv: https://arxiv.org/abs/1805.08418 · HTML: https://mlsanity.com/paper/1805.08418/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 May 2018.

## Built on by (most cited first, 1 of 1)

- [Decentralized Online Learning in Task Assignment Games for Mobile Crowdsensing](https://mlsanity.com/paper/2309.10594/) (2023)

## Abstract (arXiv)

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.