摘要：With the continuous development of wireless communication and mobile positioning technologies, spatio-temporal queries of moving objects attract more and more attention. In practical application, affected by the sampling frequency of the devices, the position information of moving objects restricted to the road network is often with uncertainty. In this paper, on the basis of the distributed computing framework-Hadoop, it firstly constructs the UPBI index mixing certain and uncertain data. Secondly, it proposes the probabilistic range parallel queries algorithm and the probabilistic calculating method of moving objects on road network. Finally, it gives space constraint r-Restrict to reduce the query scope of the possible path, and simultaneously gives sample pair division to resolve the problem of repetitive calculation. The experiment proves that index and query algorithm proposed effectively solve the mass data problem about moving objects, and enhance query efficiency and precision.
关键词：Hadoop; moving objects on road network; probabilistic range queries; ;uncertain data; sampling frequency
