Research Of Crowd Sensing Incentive Algorithm Based On Voting Mechanism

Based on the practical application,this paper aims to solve the low task performance of participants in the existing incentive mechanism through executive capability of crowd sensing and its incentive mechanism.Combined with the auction model and voting mechanism,inspire user actively participates in the crowd sensing system,and supervises the participating users to upload high-quality sensory data,thus designing a new crowd sensing incentive mechanism.The main research contents and contributions of this paper are as follows:(1)In-depth study of the network mechanism of crowd sensing and the incentive mechanism of crowd sensingThis paper systematically studies the basic network structure,basic characteristics,workflow and some typical applications of crowd sensing.The research focuses on the crowd sensing incentive mechanism,including the scope of the incentive mechanism in the group-aware network and the classification of the group-sensing incentive mechanism under the current research.And some classic crowd sensing incentive mechanism models based on anti-auction are studied in detail,and the advantages and disadvantages of these mechanisms are expounded respectively.At the same time,four defects of existing research are summarized and analyzed briefly by analyzing the classical crowd sensing incentive mechanism.(2)An improved anti-auction model based crowd sensing incentive mechanism participant decision algorithmAiming at the shortcomings of the traditional crowd sensing incentive model in the participant selection stage,an improved participant decision-making algorithm PDA based on the anti-auction model is proposed.The PDA introduces factors such as the user's task execution ability,based on the ratio of the user's bid value to the user's task execution ability,improves the participant's selection decision factor,and determines the optimal participant set according to the platform requirements,thereby achieving the selected participant.The expected purpose of high task execution ability and low bidding value.Experiments show that the participants of the PDA algorithm in this paper have a significant improvement in the task execution ability of the participants compared with the traditional auction-based crowd sensing incentive mechanism,and the PDA algorithm proposed in this paper also meets the platform budget balance.(3)A task evaluation algorithm based on voting mechanism is proposedIn this paper,For the existing crowd sensing incentive mechanism can not evaluate the participants and the perceived results of the task after the end of perception,proposes a crowd sensing task evaluation algorithm EA based on voting mechanism.There are three functions of the EA algorithm.The first is to evaluate the credibility of the task perception results through the voting mechanism,the second is to evaluate the participants' task execution ability through the voting mechanism,and the third is reward mechanism for determining the amount of the reward based on the participant's task completion degree.The experimental results show that the proposed EA algorithm can effectively evaluate the credibility of the task.The proposed EA algorithm can effectively evaluate the task execution ability of the participants to provide reference for the next decision-making stage of the group-aware participants.The EA algorithm can effectively supervise participants and enable participants to upload high-quality sensory data.