scholarly journals Efficient Key-Value Data Placement for ZNS SSD

2021 ◽  
Vol 11 (24) ◽  
pp. 11842
Author(s):  
Gijun Oh ◽  
Junseok Yang ◽  
Sungyong Ahn

Log-structured merge-tree (LSM-Tree)-based key–value stores are attracting attention for their high I/O (Input/Output) performance due to their sequential write characteristics. However, excessive writes caused by compaction shorten the lifespan of the Solid-state Drive (SSD). Therefore, there are several studies aimed at reducing garbage collection overhead by using Zoned Namespace ZNS; SSD in which the host can determine data placement. However, the existing studies have limitations in terms of performance improvement because the lifetime and hotness of key–value data are not considered. Therefore, in this paper, we propose a technique to minimize the space efficiency and garbage collection overhead of SSDs by arranging them according to the characteristics of key–value data. The proposed method was implemented by modifying ZenFS of RocksDB and, according to the result of the performance evaluation, the space efficiency could be improved by up to 75%.

Author(s):  
Chihiro Matsui ◽  
Asuka Arakawa ◽  
Chao Sun ◽  
Tomoko Ogura Iwasaki ◽  
Ken Takeuchi

Author(s):  
Jungmin Seo ◽  
Jupyung Lee ◽  
Boncheol Gu ◽  
Hyun-Jung Shin ◽  
B. M. Jung

1999 ◽  
Vol 34 (3) ◽  
pp. 37-48 ◽  
Author(s):  
Trishul M. Chilimbi ◽  
James R. Larus

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 486
Author(s):  
Yongjae Chun ◽  
Kyeore Han ◽  
Youpyo Hong

Owing to their advantages over hard disc drives (HDDs), solid-state drives (SSDs) are widely used in many applications, including consumer electronics and data centers. As erase operations are feasible only in block units, modification or deletion of pages cause invalidation of the pages in their corresponding blocks. To reclaim these invalid pages, the valid pages in the block are copied to other blocks, and the block with the invalid pages is initialized, which adversely affects the performance and durability of the SSD. The objective of a multi-stream SSD is to group data by their expected lifetimes and store each group of data in a separate area called a stream to minimize the frequency of wasteful copy-back and initialization operations. In this paper, we propose an algorithm that groups the data based on input/output (I/O) types and rewrite frequency, which show significant improvements over existing multi-stream algorithms not only for performance but also for effectiveness in covering most applications.


2018 ◽  
Vol 39 (12) ◽  
pp. 1908-1911
Author(s):  
Eung Chang Lee ◽  
Jinsung Rho ◽  
Heeyoub Kang ◽  
Bong Jae Lee

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