Updating and Querying Databases that Track Mobile Units
Distributed and Parallel Databases - Special issue on mobile data management and applications
A Framework for Generating Network-Based Moving Objects
Geoinformatica
Real-Time Traffic Updates in Moving Objects Databases
DEXA '02 Proceedings of the 13th International Workshop on Database and Expert Systems Applications
Group-Based Location Management Scheme in Personal Communication Networks
ICOIN '02 Revised Papers from the International Conference on Information Networking, Wireless Communications Technologies and Network Applications-Part II
DASFAA '01 Proceedings of the 7th International Conference on Database Systems for Advanced Applications
Managing Moving Objects on Dynamic Transportation Networks
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Techniques for Efficient Road-Network-Based Tracking of Moving Objects
IEEE Transactions on Knowledge and Data Engineering
Aqua: an adaptive QUery-Aware location updating scheme for mobile objects
DASFAA'05 Proceedings of the 10th international conference on Database Systems for Advanced Applications
Update-efficient indexing of moving objects in road networks
Geoinformatica
Hi-index | 0.00 |
Advances in wireless sensors and position technologies such as GPS enable location-based services that rely on the tracking of continuously changing positions of moving objects. The key issue in tracking techniques is how to minimize the number of updates, while providing accurate locations for query results. In this paper, for tracking network-constrained moving objects, we first propose a simulation-based prediction model with more accurate location prediction for objects movements in a traffic road network, which lowers the update frequency and assures the location precision. Then, according to their predicted future functions, objects are grouped and only the central object in each group reports its location to the server. The group update strategy further reduces the total number of objects reporting their locations. A simulation study has been conducted and proved that the group update policy based on the simulation prediction is superior to traditional update policies with fewer updates and higher location precision.