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
Xmas: an extensible main-memory storage system
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
Cleaning policies in mobile computers using flash memory
Journal of Systems and Software
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
Endurance enhancement of flash-memory storage systems: an efficient static wear leveling design
Proceedings of the 44th annual Design Automation Conference
An index rewriting scheme using compression for flash memory database systems
Journal of Information Science
Architectures and optimization methods of flash memory based storage systems
Journal of Systems Architecture: the EUROMICRO Journal
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Flash memories are one of the best media to support portable and desktop computers' storage areas. Their features include non-volatility, low power consumption, and fast access time for read operations, features 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 memory operations compared to RAM memory. In order to achieve this goal, we propose a new index management scheme based on a compressed hot-cold clustering called CHC-Tree. The CHC-Tree-based index management scheme improves index operation performance by compressing the flash index nodes and clustering the hot-cold segments. The cold cluster compression techniques using unused free area in index node reduces the number of slow write operations in index node insert/delete processes. Our performance evaluation shows that our scheme significantly reduces the write operation overheads, improving the index update performance of B-Tree by 21.9%.