The modeling of big traffic data processing based on cloud computing
The research progress of data acquisition technology and large data processing model has an important contribution to the development of urban traffic data. The control of urban transportation depends on the effective processing of real-time traffic observation data, which is usually the nature of data intensive. We study a large number of floating car data processing (FCD) traffic control in the cloud computing environment, to solve the problem of the new cloud computing technology to solve the problem of urban traffic control system. The experimental results show that the cloud computing technology such as HBase and MapReduce can provide big data flow calculation of substantial utility, such as scalability and real-time calculation performance can be accurately by our proposed data storage, management and parallel processing model. The applicability and practicability of cloud computing are evaluated for two typical data calculation tasks of urban traffic monitoring, namely FCD query, FCD map matching.