Research On Incentive Mechanism Of Group Intelligence Perception Network Based On Opportunity Transmission

With the development of mobile technology and sensor technology,the mobile devices integrate a lot of sensors.Mobile sensing takes advantage of the computing and sensing capabilities of these mobile devices in place of traditional sensor nodes for data collection.The emergence of mobile perception and crowdsourcing ideas has spawned a new kind of perceptual network called mobile crowd sensing.Crowd sensing is a"human-centered" sensing model.Compared with the traditional sensor network,its perceived node has the characteristics of mobility,sociality and selfishness.Therefore,how to motivate users to accomplish the task is one of the main points in the research of the group-based crowd sensing.Most of the users selected by the task of the crowd sensing are densely distributed and meet frequently.The opportunity and data transmission using short-range wireless communication technologies of the mobile terminal(such as Bluetooth and Wi-Fi)will greatly save the task budget.In this paper,we propose a kind of CoES mechanism by researching and analyzing the incentive mechanism of crowd sensing and opportunistic transmission.At the beginning of the mission,CoES divides the users into two types by genetic algorithm based on the perceived data amount,trajectory and pre-incentive cost of the user.Different types of users collaborate through opportunity transmission to achieve the effect of saving traffic.In the data upload stage,CoES propose incentive mechanism(10R)based on compensation of user equipment consumption,and the motivation strategy(PIM)based on increasing user's motivation about uploaded data by opportunity transmission.Finally,achieve the dual effect of cost saving and moti-vate users.The IOR incentive strategy is based on the amount of data uploaded by the user acting as an opportunistic relay and the power of the device,analyzing the amount of their collaborative tasks and rewarding,and encouraging the users to collaborate.PIM incentive mechanism is to stimulate users to actively upload data by analyzing the average upload time of user-perceived data.Finally,we use the MIT's Reality Mining data set to experiment.The results show that the CoES scheme has better performance than the direct-assignment and the ecoSense scheme in cost saving and incentive users.