학술논문

Budget-Feasible Mechanisms in Two-Sided Crowdsensing Markets: Truthfulness, Fairness, and Efficiency
Document Type
Periodical
Source
IEEE Transactions on Mobile Computing IEEE Trans. on Mobile Comput. Mobile Computing, IEEE Transactions on. 22(12):6938-6955 Dec, 2023
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
Signal Processing and Analysis
Crowdsensing
Sensors
Procurement
Biological system modeling
Costs
Mobile handsets
Resource management
Budget feasible mechanism
fairness
incentive mechanism design
mobile crowdsensing
two-sided markets
Language
ISSN
1536-1233
1558-0660
2161-9875
Abstract
In a crowdsensing platform, users are invited to provide data services, and multiple requesters compete for desired services. Due to users’ costs of providing services, it is critical to design incentive mechanisms to incentivize users with (monetary) rewards. Meanwhile, requesters may have individual budgets and compete for services with different procurement abilities. Such a setting falls into the budget-feasible mechanism design. However, most of the existing budget-feasible mechanisms focus on one-sided markets with a single requester rather than the two-sided markets with multiple requesters having different procurement abilities. Moreover, requesters and users can be selfish and strategic with their private information, which requires preventing information manipulation on both requesters’ and users’ sides. In this paper, we investigate budget-feasible mechanisms in two-sided crowdsensing markets where multiple strategic requesters come with private budgets to obtain services from the strategic users. We also consider the fairness on the requesters’ side, i.e., a requester with more budget should obtain more service. We propose budget-feasible mechanisms for two models by distinguishing the types of services, i.e., the homogeneous or heterogeneous services. All proposed mechanisms satisfy fairness, budget feasibility, truthfulness on both users’ and requesters’ sides, and the constant approximation ratio. Numerical experiment results further demonstrate the efficiency of our proposed mechanisms.