干旱区生态环境知识资源中心(Arid): Oasis: Online All-Phase Quality-Aware Incentive Mechanism for MCS

Arid

DOI	10.1109/TSC.2024.3354240
	Oasis: Online All-Phase Quality-Aware Incentive Mechanism for MCS
	Zhang, Man; Li, Xinghua; Miao, Yinbin; Luo, Bin; Ma, Siqi; Choo, Kim-Kwang Raymond; Deng, Robert H.
通讯作者	Li, XH
来源期刊	IEEE TRANSACTIONS ON SERVICES COMPUTING
ISSN	1939-1374
出版年	2024
卷号	17 期号:2 页码:589-603
英文摘要	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.
英文关键词	Task analysis Sensors Data integrity Recruitment Costs Resumes Reliability Knapsack secretary mobile crowdsensing online recruit quality-aware incentive mechanisms
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:001200148000002
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering
WOS研究方向	Computer Science
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/404154
推荐引用方式 GB/T 7714	Zhang, Man,Li, Xinghua,Miao, Yinbin,et al. Oasis: Online All-Phase Quality-Aware Incentive Mechanism for MCS[J],2024,17(2):589-603.
APA	Zhang, Man.,Li, Xinghua.,Miao, Yinbin.,Luo, Bin.,Ma, Siqi.,...&Deng, Robert H..(2024).Oasis: Online All-Phase Quality-Aware Incentive Mechanism for MCS.IEEE TRANSACTIONS ON SERVICES COMPUTING,17(2),589-603.
MLA	Zhang, Man,et al."Oasis: Online All-Phase Quality-Aware Incentive Mechanism for MCS".IEEE TRANSACTIONS ON SERVICES COMPUTING 17.2(2024):589-603.