Research On Incentive Mechanism Of Mobile Crowdsourcing System

Mobile crowdsourcing makes full use of the collaborative capabilities of mobile intelligent terminals,making it a broad application prospect in many fields such as the Internet of Things(IoT),artificial intelligence,and cloud computing.The widespread use of mobile crowdsourcing is based on the large-scale mobile user.However,users participating in the mobile crowdsourcing task will not only consume the power,memory and CPU resources of their mobile devices,but also bear the security risks of privacy exposure.If mobile users not get any rewards,it will affect their positivity for participating in the mobile crowdsourcing task.Therefore,the design of incentive mechanism is very important for the wide application of mobile crowdsourcing.This thesis mainly takes mobile crowdsourcing application and incentive mechanism as the research background,and designs different incentive mechanisms for two types of mobile crowdsourcing applications,energy harvesting and indoor fingerprint location.Aiming at the mobile crowdsourcing application scenarios of energy harvesting tasks,this thesis proposes an incentive mechanism based on contract theory to attract mobile users to contribute radio frequency(RF)energy of mobile phones.The scheme takes into account some important characteristics of mobile users,namely the time cost of mobile users,the remaining battery power,etc.,and classifies mobile users according to these characteristics.In order to overcome the information asymmetry caused by mobile users due to privacy protection,this thesis designs an optimal contract,which can prompt mobile users to choose their own type of contract items.The final simulation results show the feasibility and effectiveness of the scheme.Aiming at the mobile crowdsourcing application scenarios of indoor fingerprint location task,in order to stimulate mobile users to contribute indoor trajectory data,this thesis proposes an incentive mechanism based on the Walrasian equilibrium.The general traditional incentive mechanism is platform-centric,and the task initiators dominates the entire task process,trying to minimize the total cost of its own expenses.This will result in the mobile user being in a passive position,resulting in unfairness for mobile users.Compared with the traditional incentive mechanism,the incentive mechanism designed in this thesis can maximize the utility of all participants and system social welfare,and the whole system can reach the Pareto optimal points.In addition,this thesis also designs a distributed iterative algorithm to calculate the Walrasian equilibrium when the cloud platform is available.The final simulation results verify the convergence,optimality and robustness of the proposed algorithm.