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
Fundamentals of database systems (2nd ed.)
Fundamentals of database systems (2nd ed.)
Xmas: an extensible main-memory storage system
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
A New Flash Memory Management for Flash Storage System
COMPSAC '99 23rd International Computer Software and Applications Conference
T-Tree or B-Tree: Main Memory Database Index Structure Revisited
ADC '00 Proceedings of the Australasian Database Conference
An Adaptive Striping Architecture for Flash Memory Storage Systems of Embedded Systems
RTAS '02 Proceedings of the Eighth IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'02)
Cost-Efficient Memory Architecture Design of NAND Flash Memory Embedded Systems
ICCD '03 Proceedings of the 21st International Conference on Computer Design
An efficient R-tree implementation over flash-memory storage systems
GIS '03 Proceedings of the 11th ACM international symposium on Advances in geographic information systems
An index management using CHC-cluster for flash memory databases
Journal of Systems and Software
Survey of indexing schemes for information retrieval on flash memory based wireless sensor networks
Proceedings of the 2009 conference on Information Science, Technology and Applications
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Flash memories are one of the best media to support portable computers' storage areas in mobile database environments. Their features include non-volatility, low power consumption, and fast access time for read operations, which are sufficient to present flash memories as major database storage components for portable computers. However, we need to improve traditional index management schemes based on B-Tree due to the relatively slow characteristics of flash operations, as compared to RAM memory. In order to achieve this goal, we propose a new index rewriting scheme based on a compressed index called F-Tree. F-Tree-based index management improves index operation performance by compressing pointers and keys in tree nodes and rewriting the nodes without a slow erase operation in node insert/delete processes. Based on the results of the performance evaluation, we conclude that the F-Tree-based scheme outperforms the traditional schemes.