Distributed Task Scheduling And Incentive Mechanism Design Based On Potential Game For Mobile Crowdsensing

With the popularity of sensing technology and the latest advances in transmission technology,we are rapidly entering the Internet of Things era.The Internet of Things uses sensor units to collect a variety of information,the purpose of which is to establish a network of airtight perceptions in the real world.Traditional sensor networks require a large number of sensor nodes to be deployed to ensure area coverage and communication connections for large-scale sensing.To save costs and increase space-time coverage,the Group-aware network uses a mobile device embedded with a variety of powerful sensors to build a giant network.The traditional group intelligence perception realizes the “platform-centric” perception mode,and the platform makes task scheduling decisions,while the new perceptual technology creates a “user-centric” perception mode,that is,the task scheduling decision is made by the user.In order to further study the task scheduling mode and incentive mechanism,comparing the advantages and disadvantages of the two modes and designing the incentive mechanism is the focus of this paper.The main task of this research is to establish a model to compare the two perception modes and design the incentive mechanism.In this work,we consider a generic group-aware model consisting of multiple tasks and multiple mobil e device users.The model conforms to three major characteristics.First,each character and each device has a specific location.Second,each task and device has a certain range of survival time.Third,different devices complete different tasks.The quality and cost are not necessarily the same.Based on this model,we request a global optimal solution based on central task scheduling,establish a game model about user distributed task scheduling,and obtain a game equilibrium solution through potential game theory.Through simulation analysis,the gap between the two is compared,which provides the basis and reference for the design of the incentive mechanism below.Based on the research of scheduling scheme,this paper further studies the tax-based incentive mechanism.We have proposed a new tax framework to achieve our goals.The key idea is how to design a reasonable incentive mechanism to drive the user to make a reasonable strategy to make the game equilibrium solution approach or achieve the global o ptimal solution.We have designed the scheme of the taxation mechanism in detail,and gave the optimal taxation scheme,which proves that the game equilibrium solution can fully realize the global optimal solution.In summary,this paper compares two task scheduling models,and studies the new incentive mechanism for the gap,and analyzes the applicability of the model and the pertinence of the incentive mechanism based on the simulation results,and collects and correlates the data in the mobile group perc eption.The research provides theoretical support.