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

05/22/2018
by   Jiangtao Wang, et al.
0

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.

READ FULL TEXT

page 2

page 12

research
05/22/2018

Crowd-Powered Sensing and Actuation in Smart Cities: Current Issues and Future Directions

With the advent of seamless connection of human, machine, and smart thin...
research
09/20/2021

Crowdsourcing Diverse Paraphrases for Training Task-oriented Bots

A prominent approach to build datasets for training task-oriented bots i...
research
09/02/2019

CrowdOS: A Ubiquitous Operating System for Crowdsourcing and Mobile Crowd Sensing

With the rise of crowdsourcing and mobile crowdsensing techniques, a lar...
research
03/07/2019

Accurate inference of crowdsourcing properties when using efficient allocation strategies

Allocation strategies improve the efficiency of crowdsourcing by decreas...
research
08/03/2015

When Crowdsourcing Meets Mobile Sensing: A Social Network Perspective

Mobile sensing is an emerging technology that utilizes agent-participato...
research
09/01/2017

Adversarial Task Allocation

The problem of allocating tasks to workers is of long standing fundament...
research
01/30/2017

Dynamic Task Allocation for Crowdsourcing Settings

We consider the problem of optimal budget allocation for crowdsourcing p...

Please sign up or login with your details

Forgot password? Click here to reset