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[Author] Sang-Ho HWANG(2hit)

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  • Migration Cost Sensitive Garbage Collection Technique for Non-Volatile Memory Systems

    Sang-Ho HWANG  Ju Hee CHOI  Jong Wook KWAK  

     
    LETTER-Software System

      Pubricized:
    2016/09/12
      Vol:
    E99-D No:12
      Page(s):
    3177-3180

    In this letter, we propose a garbage collection technique for non-volatile memory systems, called Migration Cost Sensitive Garbage Collection (MCSGC). Considering the migration overhead from selecting victim blocks, MCSGC increases the lifetime of memory systems and improves response time in garbage collection. Additionally, the proposed algorithm also improves the efficiency of garbage collection by separating cold data from hot data in valid pages. In the experimental evaluation, we show that MCSGC yields up to a 82% improvement in lifetime prolongation, compared with existing garbage collection, and it also reduces erase and migration operations by up to 30% and 29%, respectively.

  • RbWL: Recency-Based Static Wear Leveling for Lifetime Extension and Overhead Reduction in NAND Flash Memory Systems

    Sang-Ho HWANG  Jong Wook KWAK  

     
    LETTER-Software System

      Pubricized:
    2018/07/09
      Vol:
    E101-D No:10
      Page(s):
    2518-2522

    In this letter, we propose a static wear leveling technique, called Recency-based Wear Leveling (RbWL). The basic idea of RbWL is to execute static wear leveling at minimum levels, because the frequent migrations of cold data by static wear leveling cause significant overhead in a NAND flash memory system. RbWL adjusts the execution frequency according to a threshold value that reflects the lifetime difference of the hot/cold blocks and the total lifetime of the NAND flash memory system. The evaluation results show that RbWL improves the lifetime of NAND flash memory systems by 52%, and it also reduces the overhead of wear leveling from 8% to 42% and from 13% to 51%, in terms of the number of erase operations and the number of page migrations of valid pages, respectively, compared with other algorithms.