摘要
The ubiquity of mobile devices have promoted the prosperity of mobile crowd systems, which recruit crowds to contribute their resources for performing tasks. Yet, due to the various resource consumption, the crowds may be reluctant to join and contribute information. Thus, the low participation level of crowds will be a hurdle that prevents the adoption of crowdsourcing. A critical challenge for these systems is how to design a proper mechanism such that the crowds spontaneously act as suppliers to contribute accurate information. Most of existing mechanisms ignore either the honesty of crowds or requesters respectively. In this paper, considering the honesty of both, we propose a game-based incentive mechanism, namely RTRC, to stimulate the crowds to contribute accurate information and to motivate the requesters to return accurate feedbacks. In addition, an evolutionary game is designed to model the dynamic of user-strategy selection. Specially, the replicator dynamic is applied to model the adaptation of strategy interactions taking into account the dynamic nature in time dependence and we also derive the evolutionarily stable strategies(ESSs) for users. Finally, empirical results over the simulations show that all the requesters and suppliers will select honest strategy to maximize their profit.
The ubiquity of mobile devices have promoted the prosperity of mobile crowd systems, which recruit crowds to contribute their resources for performing tasks. Yet, due to the various resource consumption, the crowds may be reluctant to join and contribute information. Thus, the low participation level of crowds will be a hurdle that prevents the adoption of crowdsourcing. A critical challenge for these systems is how to design a proper mechanism such that the crowds spontaneously act as suppliers to contribute accurate information. Most of existing mechanisms ignore either the honesty of crowds or requesters respectively. In this paper, considering the honesty of both, we propose a game-based incentive mechanism, namely RTRC, to stimulate the crowds to contribute accurate information and to motivate the requesters to return accurate feedbacks. In addition, an evolutionary game is designed to model the dynamic of user-strategy selection. Specially, the replicator dynamic is applied to model the adaptation of strategy interactions taking into account the dynamic nature in time dependence and we also derive the evolutionarily stable strategies（ESSs） for users. Finally, empirical results over the simulations show that all the requesters and suppliers will select honest strategy to maximize their profit.
基金
supported by the National Natural Science Foundation of China (Grant Nos. 61672408, U1405255, 61502368, 61602537, 61602357, 61672413, U1509214, U1135002)
National High Technology Research and Development Program (863 Program) (Grant Nos. 2015AA016007, 2015AA017203)
China Postdoctoral Science Foundation Funded Project (Grant No.2016M592762)
Shaanxi Science & Technology Coordination & Innovation Project (Grant No.2016TZC-G-6-3)
Shaanxi Provincial Natural Science Foundation (Grant Nos. 2015JQ6227, 2016JM6005)
China 111 Project (Grant No. B16037)
Beijing Municipal Social Science Foundation(Grant No. 16XCC023)
Fundamental Research Funds for the Central Universities (Grant Nos. JB150308, JB150309, JB161501, JBG161511)
