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Real-time garbage collection for flash-memory storage systems of real-time embedded systems
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Source ACM Transactions on Embedded Computing Systems (TECS) archive
Volume 3 ,  Issue 4  (November 2004) table of contents
Pages: 837 - 863  
Year of Publication: 2004
ISSN:1539-9087
Authors
Li-Pin Chang  National Taiwan University, Taipei, Taiwan
Tei-Wei Kuo  National Taiwan University, Taipei, Taiwan
Shi-Wu Lo  National Taiwan University, Taipei, Taiwan
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 32,   Downloads (12 Months): 235,   Citation Count: 14
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ABSTRACT

Flash-memory technology is becoming critical in building embedded systems applications because of its shock-resistant, power economic, and nonvolatile nature. With the recent technology breakthroughs in both capacity and reliability, flash-memory storage systems are now very popular in many types of embedded systems. However, because flash memory is a write-once and bulk-erase medium, we need a translation layer and a garbage-collection mechanism to provide applications a transparent storage service. In the past work, various techniques were introduced to improve the garbage-collection mechanism. These techniques aimed at both performance and endurance issues, but they all failed in providing applications a guaranteed performance. In this paper, we propose a real-time garbage-collection mechanism, which provides a guaranteed performance, for hard real-time systems. On the other hand, the proposed mechanism supports non-real-time tasks so that the potential bandwidth of the storage system can be fully utilized. A wear-leveling method, which is executed as a non-real-time service, is presented to resolve the endurance problem of flash memory. The capability of the proposed mechanism is demonstrated by a series of experiments over our system prototype.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  14

Collaborative Colleagues:
Li-Pin Chang: colleagues
Tei-Wei Kuo: colleagues
Shi-Wu Lo: colleagues