Updating and Querying Databases that Track Mobile Units
Distributed and Parallel Databases - Special issue on mobile data management and applications
Querying the trajectories of on-line mobile objects
Proceedings of the 2nd ACM international workshop on Data engineering for wireless and mobile access
The Geometry of Uncertainty in Moving Objects Databases
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Databases for Tracking Mobile Units in Real Time
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Managing uncertainty in moving objects databases
ACM Transactions on Database Systems (TODS)
Querying Imprecise Data in Moving Object Environments
IEEE Transactions on Knowledge and Data Engineering
Curve-Based Representation of Moving Object Trajectories
IDEAS '04 Proceedings of the International Database Engineering and Applications Symposium
A privacy-aware trajectory tracking query engine
ACM SIGKDD Explorations Newsletter
Location-dependent query processing: Where we are and where we are heading
ACM Computing Surveys (CSUR)
Implementing a qualitative calculus to analyse moving point objects
Expert Systems with Applications: An International Journal
On Managing Very Large Sensor-Network Data Using Bigtable
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
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In recent years, many emerging database applications deal with large sets of continuously moving data objects. Since no computer system can commit continuously occurring infinitesimal changes to the database, related data management techniques view a moving object's trajectory as a sequence of discretely reported spatiotemporal points. For each pair of consecutive committed trajectory points, a spatiotemporal uncertainty region representing all possible in-between trajectory points is defined. To support trajectory queries with a non-uniform probability distribution model, the query system needs to compute (interpolate) the “most likely” trajectories in the uncertainty regions to determine the peak points of the probability distributions. This paper proposes a generalized trajectory interpolation model using parametric trajectory representations. In addition, the paper expands and investigates three practical specializations of our proposed model using a moving object with momentum, i.e., a vehicle, as the exemplar.