IVDBMS:
Developing In-Vehicle Database Management Techniques for
Efficient Vehicular Applications
As today’s vehicles are
equipped with more and more functions/applications (e.g., road
navigation, music playing, vehicle diagnosis, traveling log, and
calendar), data in a vehicle has grown rapidly in terms of both the
volume and types. Data management has become a crucial issue in
achieving efficient vehicular applications. At present, different
applications in the same vehicle adopt different proprietary ways to
manage their data, which suffers a number of drawbacks including lack
of data sharing/integration, difficulty for information exchange, and
inability for dynamic data updating. In this project, we develop
appropriate techniques to address relevant challenges for in-vehicle
data management.
Objectives
The main objective of this project is to develop
appropriate in-vehicle data management techniques and conduct
theoretical and empirical studies to evaluate their feasibility and
effectiveness in vehicular applications. Several students will be
trained with knowledge and experience in the field via the research.
Researchers from both the university and Ford will have opportunities
to exchange information and ideas on cutting-edge database management
technologies and real-world issues.
Publications
- A. Ojewole, Q. Zhu and W. Hou, "Window
Join Approximation over Data Streams with Importance Semantics", Proceedings of the ACM 15th International
Conference on Information and Knowledge Management (CIKM'06),
Arlington, VA, Nov. 6-11, 2006
- Qiang Zhu and Brahim Medjahed, "Developing
In-Vehicle Database Management Techniques for Efficient Vehicular
Applications", UMD TechDay'06,
June 7, 2006. [pdf]
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