Oasis: Online all-phase quality-aware incentive mechanism for MCS
Publication Type
Journal Article
Publication Date
1-2024
Abstract
To motivate users to submit high quality data for mobile crowdsensing (MCS), some quality-aware incentive mechanisms have been proposed, which recruit and pay users strategically. However, in the existing mechanisms, the recruitment based only on tasks matching degree leads to the ineffective insistent data quality incentive. Meanwhile, the absence of the reasonable payment strategy cannot motivate users to submit high quality data in the current task. To address the above problems, we propose an Online all-phase quality-aware incentive mechanism (Oasis) to realize the quality incentive in both recruitment and payment phases. With the knapsack secretary, Oasis first devises a quality-aware pre-budgeting recruitment strategy, which decides whether the arriving user's long-term data quality and bid satisfy the recruited criterion. Then, in the payment phase, Oasis evaluates and updates the current and long-term data qualities of users. Based on the evaluation results, a two-level payment strategy is devised employing the Myerson theorem, where users submitting higher quality data can obtain more utilities under the budget constraint. Theoretical analysis proves that Oasis satisfies economic feasibility and constant competitiveness while achieving quality incentive in recruitment and payment phases. Extensive experiments using the real-world dataset demonstrate that the sensing result accuracy of Oasis increases 67% compared with the existing works.
Keywords
Task Analysis, Sensors, Data Integrity, Recruitment, Costs, Resumes, Reliability, Knapsack Secretary, Mobile Crowdsensing, Online Recruit, Quality Aware Incentive Mechanisms
Discipline
Databases and Information Systems
Research Areas
Information Systems and Management
Publication
IEEE Transactions on Services Computing
First Page
1
Last Page
14
ISSN
1939-1374
Identifier
10.1109/TSC.2024.3354240
Publisher
Institute of Electrical and Electronics Engineers
Citation
ZHANG, Man; LI, Xinghua; MIAO, Yinbin; LUO, Bin; MA, Siqi; CHOO, Kim-Kwang Raymond; and DENG, Robert H..
Oasis: Online all-phase quality-aware incentive mechanism for MCS. (2024). IEEE Transactions on Services Computing. 1-14.
Available at: https://ink.library.smu.edu.sg/sis_research/8661
Copyright Owner and License
Authors
Additional URL
https://doi.org/10.1109/TSC.2024.3354240