Access methods for multiversion data
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Managing persistent objects in a multi-level store
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
A foundation for representing and querying moving objects
ACM Transactions on Database Systems (TODS)
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Main Memory Database Systems: An Overview
IEEE Transactions on Knowledge and Data Engineering
A Study of Index Structures for Main Memory Database Management Systems
VLDB '86 Proceedings of the 12th International Conference on Very Large Data Bases
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
On the Generation of Spatiotemporal Datasets
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
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Recently, the need for Location-Based Services (LBS) has increased due to the development and widespread use of mobile devices (e.g., PDAs, cellular phones, laptop computers, GPS, and RFID etc). The core technology of LBS is a moving-objects database that stores and manages the positions of moving objects. To search for information quickly, the database needs to contain an index that supports both real-time position tracking and management of large numbers of updates. As a result, the index requires a structure operating in the main memory for real-time processing and requires a technique to migrate part of the index from the main memory to disk storage (or from disk storage to the main memory) to manage large volumes of data. To satisfy these requirements, this paper suggests a unified index scheme unifying the main memory and the disk as well as migration policies for migrating part of the index from the memory to the disk during a restriction in memory space. Migration policy determines a group of nodes, called the migration subtree, and migrates the group as a unit to reduce disk I/O. This method takes advantage of bulk operations and dynamic clustering. The unified index is created by applying various migration policies. This paper measures and compares the performance of the migration policies using experimental evaluation.