Research output: Contribution to Journal/Magazine › Review article › peer-review
<mark>Journal publication date</mark> | 1/10/2018 |
---|---|
<mark>Journal</mark> | IEEE Internet of Things Journal |
Issue number | 5 |
Volume | 5 |
Number of pages | 11 |
Pages (from-to) | 3747-3757 |
Publication Status | Published |
Early online date | 8/08/18 |
<mark>Original language</mark> | English |
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 paper, 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.