  A large spectrum of applications such as location based services and
environmental monitoring demand efficient query processing on uncertain
databases. In this paper, we propose the probabilistic Voronoi diagram (PVD)
for processing moving nearest neighbor queries on uncertain data, namely the
probabilistic moving nearest neighbor (PMNN) queries. A PMNN query finds the
most probable nearest neighbor of a moving query point continuously. To process
PMNN queries efficiently, we provide two techniques: a pre-computation approach
and an incremental approach. In the pre-computation approach, we develop an
algorithm to efficiently evaluate PMNN queries based on the pre-computed PVD
for the entire data set. In the incremental approach, we propose an incremental
probabilistic safe region based technique that does not require to pre-compute
the whole PVD to answer the PMNN query. In this incremental approach, we
exploit the knowledge for a known region to compute the lower bound of the
probability of an object being the nearest neighbor. Experimental results show
that our approaches significantly outperform a sampling based approach by
orders of magnitude in terms of I/O, query processing time, and communication
overheads.
