A foundation for representing and querying moving objects
ACM Transactions on Database Systems (TODS)
Modeling and Querying Moving Objects
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
A Spatiotemporal Model and Language for Moving Objects on Road Networks
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Computational data modeling for network-constrained moving objects
GIS '03 Proceedings of the 11th ACM international symposium on Advances in geographic information systems
Modeling and querying moving objects in networks
The VLDB Journal — The International Journal on Very Large Data Bases
Road Networks and Their Incomplete Representation by Network Data Models
GIScience '08 Proceedings of the 5th international conference on Geographic Information Science
Moving Query Monitoring in Spatial Network Environments
Mobile Networks and Applications
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Data about moving objects is being collected in many different application domains with the help of sensor networks, and GPS-enabled devices. In most cases, the moving objects are not free to move, they are usually restricted by some spatial constraints such as Spatial Networks. Spatial networks are ubiquitous and have been widely used in transportation, traffic planning, navigation as well as in Geographical Information System (GIS) applications. In most scenarios, moving objects such as vehicles move along predefined spatial networks like transportation networks. Unfortunately, the concepts for modeling and querying objects in unconstrained spaces like an outdoor space cannot be transferred to constrained spaces like a road network due to the different features of the environments in which the spatial objects move. Further, modern positioning devices as well as mobile and sensor technology have led to large volumes of moving objects in spatial networks. Therefore, we need a database-friendly data model to explicitly model spatial networks and, more importantly, describe relative movements in these networks. In this paper, we propose a new two-layered data model called MONET (Moving Objects in NETworks) model. The lower layer is a data model for spatial networks. This data model is the prerequisite for the upper model that represents moving objects in these networks. This layered model fits well to formulate relationships between moving objects and a network in queries. A query language, called MONET QL (MONET Query Language), allows a clear description of and access to moving objects in spatial networks and to provides high-level operations on them.