Research On Vehicle Mobile Crowdsensing Network Technology Base On Urban Public Transportation

With the rapid economic growth and the accelerating pace of urban construction,the problem of "big city diseases" has become increasingly serious,and the development strategy of building "smart cities" has emerged in many countries and regions."Smart City" can integrate the core systems of urban operation into a unified platform,thus effectively managing and controlling the operation of the city and optimizing the allocation of urban resources.Among them,the establishment of a full-coverage city-aware network is the key to building a "smart city" that can perform data collection,data transmission,and provide information services,integrating spatially discrete and temporally discontinuous information into unified intelligence.On the platform,the management efficiency and service quality of the city are significantly improved.However,how to build a fully-covered city-aware network is an urgent problem we need to solve.In order to promote the construction process of "smart city",this paper conducts an in-depth study on the vehicle-based mobile crowdsensing network technology based on urban public transportation.Firstly,this paper illustrates the advantages and disadvantages of mobile crowdsensing networks in building smart cities by comparing the advantages and disadvantages of wireless sensor networks and mobile crowdsensing networks.Then,the system composition,sensing scale,typical application and key issues of the mobile crowdsensing network are introduced in detail.The mobile sensing participant selection strategy is the research focus of this paper.In addition,the information access technologies commonly used in mobile crowdsensing networks are also introduced.In order to achieve the full coverage of urban sensing,this paper builds an urban sensing model based on urban public transportation and mobile crowdsensing technology.The model is divided into sensing layer,transport layer and application layer.On the basis of the urban sensing model,the urban public transportation is used as the participant of the mobile crowdsensing system,and the relationship between the current trajectory of the perceived participants and the future movement traj ectory,the sensing cost of the task publisher and the sensing benefit are constructed.The vehicle-based mobile crowdsensing system model,namely the spatial coverage model,is used to mathematically describe the problem selected by the participants in the vehicle-mobile crowdsensing network.Finally,through the method of problem specification,it is proved that the participant selection problem has NP-hard characteristics.In order to select the optimal sensing vehicle set to complete the sensing task in polynomial time,a participant selection strategy based on enumeration and greedy algorithm is proposed,which optimizes the quality of sensing information,ie maximizes spatial-temporal sensing coverage,when the task initiator’s sensing cost is limited.It also proves that the EGCA algorithm has the lowest performance guarantee and carries out simulation verification.