TY - GEN
T1 - CrowdTasker
T2 - 13th IEEE International Conference on Pervasive Computing and Communications, PerCom 2015
AU - Xiong, Haoyi
AU - Zhang, Daqing
AU - Chen, Guanling
AU - Wang, Leye
AU - Gauthier, Vincent
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/1
Y1 - 2015/7/1
N2 - This paper proposes a novel task allocation framework, CrowdTasker, for mobile crowdsensing. CrowdTasker operates on top of energy-efficient Piggyback Crowdsensing (PCS) task model, and aims to maximize the coverage quality of the sensing task while satisfying the incentive budget constraint. In order to achieve this goal, CrowdTasker first predicts the call and mobility of mobile users based on their historical records. With a flexible incentive model and the prediction results, CrowdTasker then selects a set of users in each sensing cycle for PCS task participation, so that the resulting solution achieves near-maximal coverage quality without exceeding incentive budget. We evaluated CrowdTasker extensively using a large-scale real-world dataset and the results show that CrowdTasker significantly outperformed three baseline approaches by achieving 3%-60% higher coverage quality.
AB - This paper proposes a novel task allocation framework, CrowdTasker, for mobile crowdsensing. CrowdTasker operates on top of energy-efficient Piggyback Crowdsensing (PCS) task model, and aims to maximize the coverage quality of the sensing task while satisfying the incentive budget constraint. In order to achieve this goal, CrowdTasker first predicts the call and mobility of mobile users based on their historical records. With a flexible incentive model and the prediction results, CrowdTasker then selects a set of users in each sensing cycle for PCS task participation, so that the resulting solution achieves near-maximal coverage quality without exceeding incentive budget. We evaluated CrowdTasker extensively using a large-scale real-world dataset and the results show that CrowdTasker significantly outperformed three baseline approaches by achieving 3%-60% higher coverage quality.
UR - https://www.scopus.com/pages/publications/84942595810
U2 - 10.1109/PERCOM.2015.7146509
DO - 10.1109/PERCOM.2015.7146509
M3 - Conference contribution
AN - SCOPUS:84942595810
T3 - 2015 IEEE International Conference on Pervasive Computing and Communications, PerCom 2015
SP - 55
EP - 62
BT - 2015 IEEE International Conference on Pervasive Computing and Communications, PerCom 2015
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 23 March 2015 through 27 March 2015
ER -