The design and analysis of spatial data structures
The design and analysis of spatial data structures
Indexing the positions of continuously moving objects
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Range and kNN query processing for moving objects in grid model
Mobile Networks and Applications
SINA: scalable incremental processing of continuous queries in spatio-temporal databases
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
STRIPES: an efficient index for predicted trajectories
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Managing uncertainty in moving objects databases
ACM Transactions on Database Systems (TODS)
Maintenance of K-nn and spatial join queries on continuously moving points
ACM Transactions on Database Systems (TODS)
Indexing spatiotemporal archives
The VLDB Journal — The International Journal on Very Large Data Bases
The TPR*-tree: an optimized spatio-temporal access method for predictive queries
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
The Bdual-Tree: indexing moving objects by space filling curves in the dual space
The VLDB Journal — The International Journal on Very Large Data Bases
Efficient Maintenance of Continuous Queries for Trajectories
Geoinformatica
Discovery of convoys in trajectory databases
Proceedings of the VLDB Endowment
Semantics and implementation of continuous sliding window queries over data streams
ACM Transactions on Database Systems (TODS)
Continuous Intersection Joins Over Moving Objects
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Optimizing moving queries over moving object data streams
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Continuous queries on trajectories of moving objects
Proceedings of the 16th International Database Engineering & Applications Sysmposium
| Hi-index | 0.00 |
Since navigation systems and tracking devices are becoming ubiquitous in our daily life, the development of efficient methods for processing massive sets of mobile objects are of utmost importance. Although future routes of mobile objects are often known in advance in many applications, this information is not fully utilized in most methods so far. In this paper, we reveal the beneficial effects of exploiting future routes for the early generation of the expected results of spatio-temporal queries. This kind of probable results is important for operative analytics in many applications like smart fleet management. In order to maintain the results of spatio-temporal queries under continuous changes of mobile objects, we present efficient methods for the maintenance of the results. Our methods make use of specific update patterns, which require substantially less maintenance costs than the most general case of an update.