Residential College | false |
Status | 已發表Published |
AIR Cache: A Variable-Size Block Cache Based on Fine-Grained Management Method | |
Li, Yuxiong1; Tan, Yujuan1,3; Xu, Congcong1; Liu, Duo1; Chen, Xianzhang1; Wang, Chengliang1; Zhou, Mingliang2; U, Leong Hou2 | |
2021 | |
Conference Name | 5th International Joint Conference on Asia-Pacific Web and Web-Age Information Management, APWeb-WAIM 2021 |
Source Publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Volume | 12859 LNCS |
Pages | 158-177 |
Conference Date | AUG 23-25, 2021 |
Conference Place | GuangZhou |
Country | China |
Author of Source | U L.H., Spaniol M., Sakurai Y., Chen J. |
Publication Place | BERLIN, GERMANY |
Publisher | Springer Science and Business Media Deutschland GmbH |
Abstract | Recently, adopting large cache blocks has received widespread attention in server-side storage caching. Besides reducing the management overheads of cache blocks, it can significantly boost the I/O throughput. However, although using large blocks has advantages in management overhead and I/O performance, existing fixed-size block management schemes in storage cache cannot effectively handle them under the complicated real-world workloads. We find that existing fixed-size block management methods will suffer from the fragmentation within the cache block and fail to identify hot/cold cache blocks correctly when adopting large blocks for caching. Therefore, aiming to solve this problem, we propose AIR cache, which is a variable-size block cache based on fine-grained management method. AIR cache contains three major parts, Multi-Granularity Writer (MGW), Multi-Granularity Eviction (MGE) and Fine-Grained Recorder (FGR) where FGR is dedicated to record the data popularity using fine-grained data sections, MGW writes data at different granularity, and MGE is responsible for evicting the data at dynamic granularity. Our experiments with real-world traces demonstrate that AIR cache can increase the read cache hit ratio by up to 6.97X and the cache space utilization rate by up to 3.63X over the traditional fixed-size block management methods. |
Keyword | Fine-grained Management Storage Cache Variable Size Block Fine-grained Management Storage Cache Variable Size Block |
DOI | 10.1007/978-3-030-85899-5_12 |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Computer Science |
WOS Subject | Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Theory & Methods |
WOS ID | WOS:000781765500012 |
Scopus ID | 2-s2.0-85115082573 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU) |
Affiliation | 1.College of Computer Science, Chongqing University, Chongqing, China 2.State Key Lab of Internet of Things for Smart City, University of Macau, Macao 3.Wuhan National Laboratory for Optoelectronics, Wuhan, China |
Recommended Citation GB/T 7714 | Li, Yuxiong,Tan, Yujuan,Xu, Congcong,et al. AIR Cache: A Variable-Size Block Cache Based on Fine-Grained Management Method[C]. U L.H., Spaniol M., Sakurai Y., Chen J., BERLIN, GERMANY:Springer Science and Business Media Deutschland GmbH, 2021, 158-177. |
APA | Li, Yuxiong., Tan, Yujuan., Xu, Congcong., Liu, Duo., Chen, Xianzhang., Wang, Chengliang., Zhou, Mingliang., & U, Leong Hou (2021). AIR Cache: A Variable-Size Block Cache Based on Fine-Grained Management Method. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12859 LNCS, 158-177. |
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