An Efficient B-Tree Layer for Flash-Memory Storage Systems

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  • 1. An Efficient B-Tree Layer for Flash-Memory Storage Systems Chin-Hsien Wu, Li-Pin Chang, and Tei-Wei Kuo The 9th International Conference on Real-Time Computing Systems and Applications (RTCSA 2003), Tainan, Taiwan 2003 발표자 : 안성용
  • 2. Introduction
    • Flash Memory
      • considered as an alternative to replace hard disk
    • B-tree
      • one of the most popular index structures because of its scalability and efficiently
    • Objective
      • We propose a module over a traditional FTL to handle intensive byte-wise operations due to B-tree access
      • BFTL (efficient B-Tree layer for flash-memory storage systems)
  • 3. Background
    • Flash Memory
      • native file-system approach
        • directly manage raw flash memory
        • JFFS/JFFS2, LFM, YAFFS
      • block-device emulation approach
        • provide a transparent block-device emulation
        • FTL/FTL-Lite
  • 4. Background
    • Flash Memory (Con’t)
      • out-place update
        • could not be over-written unless it is erase first
      • garbage collection
        • to recycle dead pages scattered over blocks
      • were-leveling
        • each block could be erased for 1 million(10 6 ) times
  • 5. Background
    • B-tree
      • tree 에 있는 각 Node 는 최대 m 개 , 최소 (m/2) 개의 종속 tree 를 가져야 한다
      • 모든 leaf Node 는 같은 level 에 있어야 한다
      • Node 의 key 값의 개수는 종속 Tree 의 개수보다 하나 적으며 최소 (m/2)-1 개 , 최대 m-1 개이다 .
    internal node: ordered list of key and linkage point leaf node: key value and record pointer
  • 6. Problem Definition
    • On hard disk
      • we usually set the size of a B-Tree node as the size which can be efficiently handled by the used block device.
      • To insert, delete, and re-balance B-Trees, B-Tree nodes are fetched from the hard disk and then written back to the original location.
      • Such operations are very efficient for hard disks.
    • On Flash Memory
      • Updating (or writing) data over flash memory is a very complicated and expensive operation.
      • Since out-place update is adopted, a whole page (512B) which contains the new version of data will be written to flash memory
  • 7. The Design and Implementation of BFTL
    • Overview
      • BFTL sits between the application layer and the block-device emulated by FTL
  • 8. The Design and Implementation of BFTL
    • reservation buffer
      • temporarily hold the newly generated records ( dirty records )
      • record deletions are handled by adding “ invalidation records ” to the reservation buffer.
      • the dirty records should be timely flushed to flash memory
    • index units
      • When dirty records are flushed, BFTL constructed “ index units ” for each dirty record
      • reflect modification of the corresponding B-Tree node
      • data_ptr, parent_node, primary_key, left_ptr, right_ptr, identifier, op_flag
      • Many index units are packed into few sectors to reduce the number of pages physically written.
      • index units of one B-Tree node could now exist in different sectors.
  • 9. The Design and Implementation of BFTL
    • index units (Con’t)
      • B-Tree node could be logically constructed by collecting and parsing all relevant index units
      • A node translation table is adopted to handle the collection of index units.
  • 10. The Design and Implementation of BFTL
    • The node Translation Table
      • maps a B-Tree node to a collection of LBA’s where the related index units reside.
      • could be re-built by scanning the flash memory when system is powered-up
  • 11. The Design and Implementation of BFTL
    • The node Translation Table
      • system parameter C
        • number of items in a list cause low performance and space overhead
        • control the maximum length of the lists of the node translation table
        • When the length of a list grows beyond C , the list will be compacted.
      • To compact a list,
        • all related index units are collected into RAM and then written back to flash memory with a smallest number of sectors.
  • 12. The Design and Implementation of BFTL
  • 13. The Design and Implementation of BFTL
    • The Commit Policy
      • how to smartly pack index units into few sectors
        • many index units should be packed together in order to further reduce the number of sectors needed
        • we also hope that index units of the same B-Tree node will not be scattered over many sectors
      • The packing problem of index units into sectors is NP-Hard.
        • The intractability of the problem could be shown by a reduction from the Bin-Packing problem
  • 14. System Analysis
    • Suppose
      • n records are to be inserted.
      • let a B-Tree node fit in a sector (provided by FTL).
      • Let H denote the current height of the B-Tree
      • N split denote the number of nodes which are split during the handling of the insertions.
      • C : maximum length of the lists
    • number of sectors read
    • number of sectors read
  • 15. Performance Evaluation
    • Experiment Setup
      • 4MB NAND flash memory
      • greedy block-recycling policy
      • fanout of B-tree: 21
      • size of a B-Tree node fits in a sector.
      • reservation buffer size: 60 records
      • maximum length of the list: 3
      • a small amount of B-Tree nodes in the top levels were cached in RAM
      • ratio rs : control the value distribution of the inserted keys
  • 16. Performance Evaluation
    • Performance of B-Tree Index Structures Creation
      • insert 24000 records
  • 17. Performance Evaluation
    • Performance of B-Tree Index Structures Creation (Con’t)
  • 18. Performance Evaluation
    • Performance of B-Tree Index Structures Maintenance
      • 24000 operation
      • we varied the ratio of the number of deletions to the number of insertions. (50/50, 40/60, 30/70, 20/80,10/90)
  • 19. Performance Evaluation
    • Size of the reservation buffer
    • Energy Consumption
  • 20. Conclusion
    • Conclusion
      • Flash-memory storage systems are very suitable for embedded systems
      • we propose a methodology and a layer design to support B-Tree index structures over flash memory.
      • BFTL reduces the number of redundant data written to flash memory.
    • Future Work
      • How to manage data records and their index structures over huge flash memory