The input/output complexity of sorting and related problems
Communications of the ACM
Randomized optimal algorithm for slope selection
Information Processing Letters
Discrete & Computational Geometry - Special issue on ACM symposium on computational geometry, North Conway
Kinetic data structures: a state of the art report
WAFR '98 Proceedings of the third workshop on the algorithmic foundations of robotics on Robotics : the algorithmic perspective: the algorithmic perspective
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
On two-dimensional indexability and optimal range search indexing
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Data structures for mobile data
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Indexing moving points (extended abstract)
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Indexing the positions of continuously moving objects
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Proceedings of the sixteenth annual symposium on Computational geometry
ACM Computing Surveys (CSUR)
Efficient searching with linear constraints
Journal of Computer and System Sciences - Special issue on the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on principles of database systems
An Efficient Multiversion Access Structure
IEEE Transactions on Knowledge and Data Engineering
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
An asymptotically optimal multiversion B-tree
The VLDB Journal — The International Journal on Very Large Data Bases
External memory data structures
Handbook of massive data sets
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
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We develop external data structures for storing points in one or two dimensions, each moving along a linear trajectory, so that a range query at a given time tq can be answered efficiently. The novel feature of our data structures is that the number of I/Os required to answer a query depends not only on the size of the data set and on the number of points in the answer but also on the difference between tq and the current time; queries close to the current time are answered fast, while queries that are far away in the future or in the past may take more time.