Research On Task Pricing Mechanism Based On Reverse Auction And Contextual Factors In MCSN

Mobile Crowdsensing Network is a new data acquisition method,which is devoted to provid universal Internet of Things services.A reasonable task pricing mechanism can not only motivate more users to participate in the sensing task,but also help the benign development of the platform,so it has gradually become a research hotspot in the field of Crowdsensing.Most existing studies of pricing mechanisms are based on historical trade records or some agent interaction in MCSN,not considering the collaborative pricing.In addition,there still exist problems such as insufficient analysis of task pricing law,large deviation of pricing prediction model,and the absence of consideration about the fine pricing of sensing tasks in online scenes.In order to solve the above problems,proposes a task pricing mechanism based on Reverse Auction and contextual factors.Firstly,the task interval pricing mechanism based on contextual factors is presented.The price interval of the sensing task is predicted by analyzing the contextual factors that affect the price variation.Using the real historical trade price set as the data source,the task pricing standard data set based on contextual factors is constructed.Natural grouping and taxonomic description of task price are realized by exploring sensing task pricing law with complex constrain relation using Two-Step Clustering Analysis.On the basis of the above,the price interval prediction model based on Deep Neural Network is implemented.The experimental results show that the predicting accuracy of the pricing mechanism is higher than 82.7 %.Secondly,a task detail pricing mechanism based on reverse auction in online scene is presented,in which task prices are determined in real time by agent interactions.Task participants submit quotation information to the platform under the guidance of IPCF to obtain eligibility to participate in the task.The platform selects the arriving task participants and determines their remuneration by Reverse Auction strategy,and introduces situation threshold to change remuneration.The results show that the mechanism can meet the characteristic conditions such as computational efficiency,improve the income of task participants,and encourage them to actively participate in sensing tasks.Finally,Design and implement MCSN prototype system based on IPCF & DPRA.The system includes: the MCSN platform publishes the Web client of the sensing task and price range,the Android mobile terminal for the task participants to complete the sensing task and obtain remuneration,and the server side for business processing.The MCSN prototype system is realized by integrating the two pricing mechanisms which have been improved from the perspective of practical application.