An efficient and parallel file defragmentation scheme for flash-based SSDs
- Authors
- Zhu, Guangyu; Lee, Jeongeun; Son, Yongseok
- Issue Date
- Apr-2022
- Publisher
- Association for Computing Machinery
- Citation
- Proceedings of the ACM Symposium on Applied Computing, pp 1208 - 1211
- Pages
- 4
- Journal Title
- Proceedings of the ACM Symposium on Applied Computing
- Start Page
- 1208
- End Page
- 1211
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/58201
- DOI
- 10.1145/3477314.3507225
- ISSN
- 0000-0000
- Abstract
- File fragmentation can increase I/O latency and decrease I/O throughput because reading a fragmented file can be followed by reading several scattered blocks. Thus, a defragmentation process is required to provide better I/O performance. However, an existing defragmentation process can be time-consuming on SSDs since it is based on HDD without consideration of SSD characteristics. For example, the process is performed by a single defragger in a serialized manner. To accelerate this defragmentation process, we propose an efficient and parallel file defragmentation scheme for flash-based SSDs. Our scheme exploits the internal parallelism of SSDs to reduce the execution time of the defragmentation process. To do this, we devise multiple defraggers to perform defragmentation and I/O operations for several files in parallel. We implement our scheme and evaluate it on a real machine with a flash-based SSD. The evaluation results show that the proposed scheme can reduce the execution time by up to 2.96x compared with an existing defragmentation tool, e4defrag. © 2022 Owner/Author.
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Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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