FAST: A generic framework for flash-aware spatial trees

Mohamed Sarwat, Mohamed F. Mokbel, Xun Zhou, Suman Nath

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Scopus citations


Spatial tree index structures are crucial components in spatial data management systems, designed with the implicit assumption that the underlying external memory storage is the conventional magnetic hard disk drives. This assumption is going to be invalid soon, as flash memory storage is increasingly adopted as the main storage media in mobile devices, digital cameras, embedded sensors, and notebooks. Though it is direct and simple to port existing spatial tree index structures on the flash memory storage, that direct approach does not consider the unique characteristics of flash memory, i.e., slow write operations, and erase-before-update property, which would result in a sub optimal performance. In this paper, we introduce FAST (i.e., Flash-Aware Spatial Trees) as a generic framework for flash-aware spatial tree index structures. FAST distinguishes itself from all previous attempts of flash memory indexing in two aspects: (1) FAST is a generic framework that can be applied to a wide class of data partitioning spatial tree structures including R-tree and its variants, and (2) FAST achieves both efficiency and durability of read and write flash operations through smart memory flushing and crash recovery techniques. Extensive experimental results, based on an actual implementation of FAST inside the GiST index structure in PostgreSQL, show that FAST achieves better performance than its competitors.

Original languageEnglish (US)
Title of host publicationAdvances in Spatial and Temporal Databases - 12th International Symposium, SSTD 2011, Proceedings
Number of pages19
StatePublished - 2011
Externally publishedYes
Event12th International Symposium on Advances in Spatial and Temporal Databases, SSTD 2011 - Minneapolis, MN, United States
Duration: Aug 24 2011Aug 26 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6849 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other12th International Symposium on Advances in Spatial and Temporal Databases, SSTD 2011
Country/TerritoryUnited States
CityMinneapolis, MN

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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