Research On Coverage And Routing Strategies In Mobile Crowd Sensing Networks

In recent years,more and more enterprises and institutions have been involved in the research of intelligent devices.With the help of a large number of mobile devices,people can produce and collect lots of data.As a major breakthrough in the rapid development of mobile Internet and wireless communication field,especially the "Internet+" concept,4G-LTE network and 5G network developing,the related research of crowdsourcing field has been perfected and developed.Different from the traditional wireless sensor networks,MCSN needs to provide a larger,more complex,lightweight,thorough and comprehensive service of sense.At present,more and more scholars and institutions have been involved in the research of mobile group intelligence perception,and there have been a variety of mobile applications.Mobile crowd sensing can accomplish large-scale and complex social perception tasks which are hard to be achieved only by individuals,but also overcome the disadvantages of the traditional methods,such as too much cost,and flexibility.The most important point of MCSN is "human centered",that is to say,the mobile device users will participate in the whole process of the task.The "human centered" reflects that people in the MCSN are not only the producers of the data,but also the consumers who perceive the data.Therefore,this paper focuses on the research of "human",that is,how to choose the appropriate mobile users to participate in the sensing tasks.This problem is the key problem to be solved urgently,which is also the main content of this paper.To solve this problem,this paper from the user recruitment strategy and routing problem,how to design coverage problem,puts forward some new ideas and methods.Research on user mobility prediction.This is the basis of all the next work,and its accuracy has a great impact on the user recruitment strategy.Mobility prediction has certain social characteristics,such as regular access to some position,so the prediction model and the algorithm can get good effect.On the other hand,the prediction needs to consider the related factors such as user perception,perception of a smaller range,mobile crowd sensing task location and often changes,so the prediction model and the algorithm need to adjust and modify.In this paper,we analyze the user's perception of the historical data,and then predict the user's mobility.Research on mobile coverage problem.Mainly from the traditional wireless sensor network coverage based on the extension of the problem in the new context to solve the new problem,in order to adapt to the requirements of mobile crowd sensing applications.In this paper,we propose an efficient user recruitment strategy based on the Markov prediction model with multi sensing location,which is aimed at the problem of the user recruitment.Research on routing method.Considering the mobile crowd sensing "human center",based on the Markov model,this paper proposes a node routing strategy based on utility value,will be recruited to combine the research on opportunistic forwarding mechanism and user.Through the study on the prediction of user mobility,and used to solve the coverage problem and routing problem in MCSN,are respectively designed optimal users recruitment strategy and routing strategy based on utility value.Based on the experiments this paper achieves the desired proposes.