An O(nlogn) implementation of the Douglas-Peucker algorithm for line simplification
SCG '94 Proceedings of the tenth annual symposium on Computational geometry
Approximating monotone polygonal curves using the uniform metric
Proceedings of the twelfth annual symposium on Computational geometry
Updating and Querying Databases that Track Mobile Units
Distributed and Parallel Databases - Special issue on mobile data management and applications
A Comparison of Protocols for Updating Location Information
Cluster Computing
Approximation of Polygonal Curves with Minimum Number of Line Segments
ISAAC '92 Proceedings of the Third International Symposium on Algorithms and Computation
Capturing the Uncertainty of Moving-Object Representations
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Techniques for Efficient Road-Network-Based Tracking of Moving Objects
IEEE Transactions on Knowledge and Data Engineering
On-line data reduction and the quality of history in moving objects databases
MobiDE '06 Proceedings of the 5th ACM international workshop on Data engineering for wireless and mobile access
Spatio-temporal data reduction with deterministic error bounds
The VLDB Journal — The International Journal on Very Large Data Bases
Sampling Trajectory Streams with Spatiotemporal Criteria
SSDBM '06 Proceedings of the 18th International Conference on Scientific and Statistical Database Management
Amnesic online synopses for moving objects
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Streaming algorithms for line simplification
SCG '07 Proceedings of the twenty-third annual symposium on Computational geometry
Preprocessing Position Data of Mobile Objects
MDM '08 Proceedings of the The Ninth International Conference on Mobile Data Management
Scalable processing of trajectory-based queries in space-partitioned moving objects databases
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Remote real-time trajectory simplification
PERCOM '09 Proceedings of the 2009 IEEE International Conference on Pervasive Computing and Communications
Online trajectory data reduction using connection-preserving dead reckoning
Proceedings of the 5th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services
Compressing spatio-temporal trajectories
ISAAC'07 Proceedings of the 18th international conference on Algorithms and computation
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Moving objects databases (MOD) manage trajectory information of vehicles, animals, and other mobile objects. A crucial problem is how to efficiently track an object's trajectory in real-time, in particular if the trajectory data is sensed at the mobile object and thus has to be communicated over a wireless network. We propose a family of tracking protocols that allow trading the communication cost and the amount of trajectory data stored at a MOD off against the spatial accuracy. With each of these protocols, the MOD manages a simplified trajectory that does not deviate by more than a certain accuracy bound from the actual movement. Moreover, the different protocols enable several trade-offs between computational costs, communication cost, and the reduction in the trajectory data: Connection-Preserving Dead Reckoning minimizes the communication cost using dead reckoning, a technique originally designed for tracking an object's current position. Generic Remote Trajectory Simplification (GRTS) further separates between tracking of the current position and simplification of the past trajectory and can be realized with different line simplification algorithms. For both protocols, we discuss how to bound the space consumption and computing time at the moving object and thereby present an effective compression technique to optimize the reduction performance of real-time line simplification in general. Our evaluations with hundreds of real GPS traces show that a realization of GRTS with a simple simplification heuristic reaches 85---90% of the best possible reduction rate, given by retrospective offline simplification. A realization with the optimal line simplification algorithm by Imai and Iri even reaches more than 97% of the best possible reduction rate.