TrickleKV: A High-Performance Key-Value Store on Disaggregated Storage With Low Network Traffic
Disaggregated storage (DS) based on remote direct memory access (RDMA) network decouples compute and storage resources, thereby significantly improving resource utilization. While building key-value (KV) stores on DS benefits from these merits, existing fast KV stores suffer from network bandwidth c...
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IEEE
2024-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10752495/ |
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| author | Ling Zhan Kai Lu Yiqin Xiong Jiguang Wan Zixuan Yang |
| author_facet | Ling Zhan Kai Lu Yiqin Xiong Jiguang Wan Zixuan Yang |
| author_sort | Ling Zhan |
| collection | DOAJ |
| description | Disaggregated storage (DS) based on remote direct memory access (RDMA) network decouples compute and storage resources, thereby significantly improving resource utilization. While building key-value (KV) stores on DS benefits from these merits, existing fast KV stores suffer from network bandwidth contention and high latency under DS due to the non-negligible network amplification and high-overhead I/O stack. In this paper, we propose TrickleKV, a high-performance persistent KV store designed for DS. TrickleKV reduces network amplification and latency in three approaches: 1) TrickleKV proposes an efficient storage-side data filtering mechanism and a two-level cache structure with different granularities to reduce network traffic in the read process. 2) TrickleKV presents an efficient write buffer structure that includes asynchronous flushing and queue scheduling mechanisms to reduce network traffic in the write process. 3) TrickleKV designs a read-write decoupled user-space I/O stack and lightweight storage space management to reduce access latency. Evaluation results show that TrickleKV achieves <inline-formula> <tex-math notation="LaTeX">$1.2\times $ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$7\times $ </tex-math></inline-formula> higher throughput and 30%-<inline-formula> <tex-math notation="LaTeX">$7.4\times $ </tex-math></inline-formula> lower latency compared to state-of-the-art KV stores under DS. |
| format | Article |
| id | doaj-art-fd9118c1f88b49dab8bfbdcbcf1263ee |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-fd9118c1f88b49dab8bfbdcbcf1263ee2025-08-20T02:32:45ZengIEEEIEEE Access2169-35362024-01-011216759616761210.1109/ACCESS.2024.349688010752495TrickleKV: A High-Performance Key-Value Store on Disaggregated Storage With Low Network TrafficLing Zhan0Kai Lu1https://orcid.org/0000-0002-7757-4083Yiqin Xiong2https://orcid.org/0009-0003-2113-7014Jiguang Wan3https://orcid.org/0000-0002-4160-9475Zixuan Yang4Faculty of Information Science and Technology, Wenhua College, Wuhan, ChinaWuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, ChinaWuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, ChinaWuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Big Data and Artificial Intelligence, Fujian Normal University, Fuzhou, ChinaDisaggregated storage (DS) based on remote direct memory access (RDMA) network decouples compute and storage resources, thereby significantly improving resource utilization. While building key-value (KV) stores on DS benefits from these merits, existing fast KV stores suffer from network bandwidth contention and high latency under DS due to the non-negligible network amplification and high-overhead I/O stack. In this paper, we propose TrickleKV, a high-performance persistent KV store designed for DS. TrickleKV reduces network amplification and latency in three approaches: 1) TrickleKV proposes an efficient storage-side data filtering mechanism and a two-level cache structure with different granularities to reduce network traffic in the read process. 2) TrickleKV presents an efficient write buffer structure that includes asynchronous flushing and queue scheduling mechanisms to reduce network traffic in the write process. 3) TrickleKV designs a read-write decoupled user-space I/O stack and lightweight storage space management to reduce access latency. Evaluation results show that TrickleKV achieves <inline-formula> <tex-math notation="LaTeX">$1.2\times $ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$7\times $ </tex-math></inline-formula> higher throughput and 30%-<inline-formula> <tex-math notation="LaTeX">$7.4\times $ </tex-math></inline-formula> lower latency compared to state-of-the-art KV stores under DS.https://ieeexplore.ieee.org/document/10752495/Disaggregated storagekey-value storeNVMe over fabricsremote direct memory access |
| spellingShingle | Ling Zhan Kai Lu Yiqin Xiong Jiguang Wan Zixuan Yang TrickleKV: A High-Performance Key-Value Store on Disaggregated Storage With Low Network Traffic IEEE Access Disaggregated storage key-value store NVMe over fabrics remote direct memory access |
| title | TrickleKV: A High-Performance Key-Value Store on Disaggregated Storage With Low Network Traffic |
| title_full | TrickleKV: A High-Performance Key-Value Store on Disaggregated Storage With Low Network Traffic |
| title_fullStr | TrickleKV: A High-Performance Key-Value Store on Disaggregated Storage With Low Network Traffic |
| title_full_unstemmed | TrickleKV: A High-Performance Key-Value Store on Disaggregated Storage With Low Network Traffic |
| title_short | TrickleKV: A High-Performance Key-Value Store on Disaggregated Storage With Low Network Traffic |
| title_sort | tricklekv a high performance key value store on disaggregated storage with low network traffic |
| topic | Disaggregated storage key-value store NVMe over fabrics remote direct memory access |
| url | https://ieeexplore.ieee.org/document/10752495/ |
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