ReLoaDing Performance: A Locality-Based Strategy for Rapid Reads in Encrypted Key-Value Systems

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：25

、訪客IP：3.144.156.43

姓名

洪季絜(Chi-Chieh Hung) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

(ReLoaDing Performance: A Locality-Based Strategy for Rapid Reads in Encrypted Key-Value Systems)

相關論文

★ 重新思考虛擬記憶體管理的方式以開放通道式固態硬碟最大限度地減少深度學習推薦系統演算法的讀寫流量	★ 開啟製程相似檢查方法在組裝超級塊上以最小化額外的寫入延遲
★ LaDy: Enabling Locality-aware Deduplication Technology on Shingled Magnetic Recording Drives	★ On Minimizing Writing Overhead to Establish a Low-latency LSM-tree on Skyrmion-based Racetrack Memory
★ WABE: Rethinking B-epsilon-tree to Minimize Write-amplification on NAND Flash Memory	★ Rethinking Bϵ tree Indexing Structure over NVM with the Support of Multi-write Modes
★ Prophet’s Insight: Unleashing Deduplication System Performance in Multi-tier Storage Systems	★ Freeing the Power of High Parallelism: Accelerating the Bϵ-Tree Indexing Scheme Performance on Open-Channel SSD
★ Applying Content-Defined Chunking to OCSSD-based Deduplication Systems	★ Jointly Consider GC Overhead and Storage Internal Parallelism to Boost ZNS SSD Performance
★ GraLoc: Preserving Graph Locality to Minimize Read and Write Amplification on NAND Flash Memory	★ On Minimizing Writing Overhead to Establish a Low-latency LSM-tree on Skyrmion-based Racetrack Memory
★ Planting a Forest in Sky: Harnessing Parallelism in Skyrmion Racetrack Memory for Efficient Random Forest Data Placement	★ LaGRange: Locality-aware Graph with Range Maintenance
★ Precision versusPerformance: Optimizing Swapping Mechanisms in Multi-Mode NVM

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 (2026-11-29以後開放)

摘要(中)

在鍵值儲存系統中，為了確保資料的安全性，常採用壓縮與加密技術來處理鍵值對。然而，將多個鍵值對進行打包以提升壓縮比和加密效率的方式，卻在僅需存取部分資料時，容易導致讀取延遲的增加。隨著時間推移，資料的存取模式不斷在改變，傳統的打包方式逐漸無法適應實際的資料區域性，導致系統需反覆解密與解壓縮大量資料，進一步造成效能損耗。本研究提出了一種名為 ReLoaD 的創新區域性重新打包策略，該策略針對高頻存取的鍵值對進行動態重新打包，不僅降低了解密與解壓縮的成本，還有效縮短了讀取延遲，全面提升了加密鍵值儲存系統的效能。實驗結果證實，ReLoaD 在確保資料安全性的同時，大幅改善了讀取效率，為打造更高效且具適應性的安全資料儲存方案提供了新方向。

摘要(英)

In key-value store systems, data security is often prioritized through compression and encryption of stored key-value pairs. However, packaging multiple key-value pairs together for improved compression ratios and encryption efficiency leads to significant read latency when only a subset of data is required. As data access patterns evolve over time, traditional storage packages no longer align with actual data locality, resulting in performance overhead due to the repeated decryption and decompression of large data units. This paper introduces ReLoaD, a novel locality-remodeling packing strategy designed to dynamically repack frequently accessed key-value pairs. By intelligently restructuring data locality, ReLoaD reduces the decryption and decompression burdens, minimizing read latency and enhancing overall performance in encrypted key-value store applications. Experimental results demonstrate that ReLoaD achieves substantial improvements in read efficiency without compromising security, paving the way for more responsive and adaptable secure data storage solutions.

關鍵字(中)

★ 鍵值儲存
★ 快閃記憶體
★ 資料安全
★ 資料加密

關鍵字(英)

★ Key-value store
★ flash memory
★ data security
★ data encryption

論文目次

摘要 i
Abstract ii
Contents iii
List of Figures iv
1. Introduction 1
2. Foundations & Motivation 4
2-1. Secure Key-value Database 4
2-2. Flash Memory Basics 5
2-3. Motivation 7
3. ReLoaD: Repacking Locality Data 10
3-1. System Overview 10
3-2. Detailed Components 12
3-3. Overhead Analysis 16
4. Experiments 18
4-1. Experimental Setup 18
4-2. Evaluation Result 21
5. Concluding Remarks 24
6. References 25

參考文獻

[1] J. Yang, Y. Yue, and K. V. Rashmi, “A large-scale analysis of hundreds of in-memory key-value cache clusters at twitter,” vol. 17, no. 3, 2021. [Online]. Available: https://doi.org/10.1145/3468521
[2] J. Idziorek, A. Keyes, C. Lazier, S. Perianayagam, P. Ramanathan, J. C. S. III, D. Terry, and A. Vig, “Distributed transactions at scale in amazon DynamoDB,” in 2023 USENIX Annual Technical Conference (USENIX ATC 23). Boston, MA: USENIX Association, Jul. 2023, pp. 705–717. [Online]. Available: https://www.usenix.org/conference/atc23/presentation/idziorek
[3] S. Qi, J. Wang, M. Miao, M. Zhang, and X. Chen, “Tinyenc: Enabling compressed and encrypted big data stores with rich query support,” IEEE Transactions on Dependable and Secure Computing, vol. 20, no. 1, pp. 176–192, 2023.
[4] W. Zheng, F. Li, R. A. Popa, I. Stoica, and R. Agarwal, “Minicrypt: Reconciling encryption and compression for big data stores,” in Proceedings of the Twelfth European Conference on Computer Systems, ser. EuroSys ’17. New York, NY, USA: Association for Computing Machinery, 2017, p. 191–204. [Online]. Available: https://doi.org/10.1145/3064176.3064184
[5] M. Qin, Q. Zheng, J. Lee, B. Settlemyer, F. Wen, N. Reddy, and P. Gratz, “Kvrangedb: Range queries for a hash-based key–value device,” ACM Trans. Storage, vol. 19, no. 3, Jun. 2023. [Online]. Available: https://doi.org/10.1145/3582013
[6] Y. Ren, J. Xie, Y. Qiu, H. Lv, W. Yin, L. Wang, B. Yu, H. Chen, X. He, Z. Liao, and X. Shi, “A low-latency multi-version key-value store using b-tree on an fpga-cpu platform,” in 2019 29th International Conference on Field Programmable Logic and Applications (FPL), 2019, pp. 321– 325
[7] X. Wu, Y. Xu, Z. Shao, and S. Jiang, “LSM-trie: An LSMtree-based Ultra-Large Key-Value store for small data items,” in 2015 USENIX Annual Technical Conference (USENIX ATC 15). Santa Clara, CA: USENIX Association, Jul. 2015, pp. 71–82. [Online]. Available: https://www.usenix.org/conference/atc15/technicalsession/presentation/wu
[8] I. Google, “Leveldb,” https://github.com/google/leveldb, 2011, accessed: 2024-11-20.
[9] Arasu, A., Blanas, S., Eguro, K., Kaushik, R., Kossmann, D., Ramamurthy, R., & Venkatesan, R. "Orthogonal Security with Cipherbase." Conference on Innovative Data Systems Research, 2013
[10] X. Yuan, Y. Guo, X. Wang, C. Wang, B. Li, and X. Jia, “Enckv: An encrypted key-value store with rich queries,” in Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security, ser. ASIA CCS ’17. New York, NY, USA: Association for Computing Machinery, 2017, p. 423–435. [Online]. Available: https://doi.org/10.1145/3052973.3052977
[11] y. GUO, X. Yuan, X. Wang, C. Wang, B. Li, and X. Jia, “Enabling encrypted rich queries in distributed key-value stores,” IEEE Transactions on Parallel and Distributed Systems, vol. 30, no. 6, pp. 1283–1297, 2019.
[12] X. Yuan, X. Wang, C. Wang, C. Qian, and J. Lin, “Building an encrypted, distributed, and searchable key-value store,” in Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security, ser. ASIA CCS ’16. New York, NY, USA: Association for Computing Machinery, 2016, p. 547–558. [Online]. Available: https://doi.org/10.1145/2897845.2897852
[13] L. Lu, T. S. Pillai, H. Gopalakrishnan, A. C. Arpaci-Dusseau, and R. H. Arpaci-Dusseau, “Wisckey: Separating keys from values in ssd-conscious storage,” ACM Trans. Storage, vol. 13, no. 1, Mar. 2017. [Online]. Available: https://doi.org/10.1145/3033273
[14] S. Nie, Y. Zhang, W. Wu, and J. Yang, “Layer rber variation aware read performance optimization for 3d flash memories,” in 2020 57th ACM/IEEE Design Automation Conference (DAC), 2020, pp. 1–6.
[15] M. Bjorling, J. Gonzalez, and P. Bonnet, “LightNVM: The linux Open-Channel SSD subsystem,” in 15th USENIX Conference on File and Storage Technologies (FAST 17). Santa Clara, CA: USENIX Association, Feb. 2017, pp. 359–374. [Online]. Available: https://www.usenix.org/conference/fast17/technicalsessions/presentation/bjorling
[16] M. Bjorling, A. Aghayev, H. Holmberg, A. Ramesh, D. L. Moal, G. R. Ganger, and G. Amvrosiadis, “ZNS: Avoiding the block interface tax for flash-based SSDs,” in 2021 USENIX Annual Technical Conference (USENIX ATC 21). USENIX Association, Jul. 2021, pp. 689–703. [Online]. Available: https://www.usenix.org/conference/atc21/presentation/bjorling
[17] S. Electronics, “Samsung z-ssd sz985 specification,” https://semiconductor.samsung.com/resources/brochure/Brochure_Samsung_S-ZZD_SZ985_1804.pdf, 2018, accessed: 2024-11-20.
[18] J. Yang, Y. Yue, and K. V. Rashmi, “A large scale analysis of hundreds of in-memory cache clusters at twitter,” in 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI 20). USENIX Association, Nov. 2020, pp. 191–208. [Online]. Available: https://www.usenix.org/conference/osdi20/presentation/yang
[19] O. Eytan, D. Harnik, E. Ofer, R. Friedman, and R. Kat, “It’s time to revisit LRU vs. FIFO,” in 12th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage 20). USENIX Association, Jul. 2020. [Online]. Available: https://www.usenix.org/conference/hotstorage20/presentation/eytan
[20] S. N. I. Association, “Storage networking industry association (snia),” https://www.snia.org, 2024, accessed: 2024-11-20.
[21] Crucial, “Crucial p1 500gb 3d nand nvme pcie m.2 ssd (ct500p1ssd8),” https://www.crucial.com/, 2018, accessed: 2024-11-20.

指導教授

陳增益(Tseng-Yi Chen)

審核日期

2024-12-3

推文