Title
Quality-Aware Incentive Mechanism for Mobile Crowd Sensing.
Abstract
Mobile crowd sensing (MCS) is a novel sensing paradigm which can sense human-centered daily activities and the surrounding environment. The impact of mobility and selfishness of participants on the data reliability cannot be ignored in most mobile crowd sensing systems. To address this issue, we present a universal system model based on the reverse auction framework and formulate the problem as the Multiple Quality Multiple User Selection (MQMUS) problem. The quality-aware incentive mechanism (QAIM) is proposed to meet the quality requirement of data reliability. We demonstrate that the proposed incentive mechanism achieves the properties of computational efficiency, individual rationality, and truthfulness. And meanwhile, we evaluate the performance and validate the theoretical properties of our incentive mechanism through extensive simulation experiments.
Year
DOI
Venue
2017
10.1155/2017/5757125
JOURNAL OF SENSORS
Field
DocType
Volume
Sensing system,Rationality,Incentive,Computer security,Data reliability,Electronic engineering,Selfishness,Engineering,Reverse auction,System model,Distributed computing
Journal
2017
ISSN
Citations 
PageRank 
1687-725X
2
0.39
References 
Authors
8
5
Name
Order
Citations
PageRank
Lingyun Jiang121.07
Fan He242.12
Yu Wang316728.47
Lijuan Sun411820.41
Haiping Huang514330.90