Research On Data Sharing Mechanism In Mobile Crowdsensing Network

With the rapid development of the Internet and smart phones,each user has one or more smart terminals,each terminal device is equipped with a variety of sensors,transmitters and receivers,etc.Due to its large number and wide distribution The application and research based on group intelligence perception is the direction that many researchers pay attention to.Smart terminal access to resources consumes data traffic and bandwidth,while mobile data traffic and transmission speed have certain limits.Therefore,the convenient acquisition and use of data traffic and the improvement of file transmission speed are very important research topics.In view of the above problems,based on the data transmission scenarios and characteristics of mobile devices,thesis proposes a scheme for data sharing with multi-user devices to improve the use of mobile data and the speed of data file transmission.Two data sharing models,one-to-many matching and many-to-many matching,are studied.The one-to-many data sharing problem is solved by the OTM algorithm based on greedy strategy.The many-to-many data sharing problem is converted into a stable matching problem and proposed based on SMP.The MTM algorithm is used to solve this problem.For the problem of multi-user collaborative data transmission,multiple intelligent devices are used to collaborate to divide a large file into multiple blocks for transmission.Mainly studied two cases of a data requester and multiple data requesters at the same time.For the first case,a GM algorithm based on greedy strategy is proposed to solve the user selection problem.For the second case,a KMI algorithm based on the minimum time difference is proposed to solve the user matching problem.A large number of experimental results show that in the data sharing scenario,our proposed scheme considers the matching difference degree,and has a better effect on the user profitability and matching difference degree.In the collaborative transmission scenario,the results show that the strategy we designed has better performance in terms of average user profitability,total data transmission,request failure rate,and time difference.