Collection-behavior based multi-parameter posted pricing mechanism for crowd sensing

Jiajun Sun, Huadong Ma

Abstract: Recently numerous sensing applications from the Internet of Things(IoT), such as traffic monitoring and noise map making, require the expensive installation cost. To handle this challenge, crowd sensing, as a new paradigm, has received extensive concerns. To achieve good service quality, incentive mechanisms are necessary to attract more users to participate in crowd sensing. However, Traditional incentive mechanisms such as the Vickrey-Clarke-Groves (VCG) mechanism and its variants, are not applicable for practical continuous crowd sensing applications, where bids cannot be solicited and only posted pricing mechanisms can be implemented. To tackle the issue, we propose a novel crowd sensing framework by applying all-pay auctions, and then design a collection-behavior based multi-parameter posted pricing mechanism by applying crowd aversion and posted pricing mechanisms. Simulation results indicate that incentive mechanisms in our proposed framework outperform the existing solution with respect to user participation and submission quality.