Research And Analysis Of Incentive Mechanism For Social Network Mobile Group Intelligent Perception

Mass perception is a hot research field in the current Internet of things and computer science.As academics and industry researchers deepen their exploration of group intelligence,they discover that by perceiving the information of multiple individuals,they discover the public information of the individual and reflect the nature of the group and thus affect the society.The basic characteristics.From the perspective of the research needs of group intelligence perception,group intelligence perception requires the analysis and research of massive data and its use as a research on human behavior.From the perspective of the characteristics of group intelligence perception,group intelligence perception has social universality;therefore,it is oriented towards the society.The study of mobile group intelligence perception in networks has important theoretical and application values for the development of mobile group intelligence perception.This article starts from the practical application background,combines the characteristics of group intelligence perception theory and its own incentive mechanism,takes participants' location information as an entry point,deeply analyzes the important influence of coverage rate on incentive mechanism,and solves the coverage problem based on participant location information.Design a fair incentive scheme for all participants,and try to establish an evolution model and an overlay model that are closer to the actual incentive mechanism;in order to achieve the purpose of improving participants' initiative and reducing the redundancy of the perceived data.Therefore,this dissertation will focus on the basic incentive mechanism of social network intelligence perception,try to study the optimization model of incentive mechanism based on location information,and solve the existing research problems.This research has important implications for the study of social networks and incentive mechanisms.significance.The main research content of this paper is as follows:(1)In-depth study of the basic theory and incentive mechanism of group perceptionThis paper analyzes the basic theory of group perception and the basic concept of incentive mechanism,systematically studies the incentive mechanism in group perception.The group-wise perception incentive mechanism has different incentive methods.From the return method,it can be divided into monetary and non-monetary incentives.Through the use of money and other valuable real objects as the main means of currency,the auction model mechanism is the classic currency incentive method;in the open model,the perceptual object quotes its own perception data,and the cloud service selects the payment quote The perception data of relatively low perceptual objects are subjected to data analysis and processing.The monetary incentive method directly rewards the perceived object using money and other valuable items,and it is also the main incentive method for current compensation payment.In this study,the monetary formula is mainly used as a late incentive.(2)Propose an optimal coverage model for the perceived area of social networks.This paper deeply analyzes the impact of participants' location information,sensor equipment coverage and participant mobility on the intelligence perception incentive mechanism,and further analyzes the incentive mechanism model based on RADP-VPC algorithm,aiming at RADP-VPC algorithm.The existing disadvantages of low coverage of location information of the participants,the high redundancy of the acquired sensing data,and the insufficiency of the collected data area are all defects.This paper proposes an improved optimal coverage ratio for the perceived area of the social network.model.The experimental results show that the model can effectively improve the coverage of participants in the sensing area through the EPMC algorithm,which has a good practical significance.(3)A location-based maximum coverage(EPMC)algorithm is proposed.Aiming at the defect of RADP-VPC based on participant position information,this paper proposes an EPMC(Equal Location-based Maximum Coverage)algorithm,which uses location information as the participant's honesty for the perception task and mathematical modeling based on location information.Analyze the feasibility of incentives in terms of coverage;at the same time,based on the EPMC model,propose an incentive program that encourages participants to actively participate in perceptual tasks.The experimental results show that compared with the traditional RADP-VPC algorithm model,the EPMC algorithm proposed in this paper has a better promoting effect on participant mobility,can effectively improve the coverage area,and can also reduce the perceived data.Redundancy can provide an effective reference for the Group's perception of incentive schemes.