ACM Transactions on Storage

Papers
(The TQCC of ACM Transactions on Storage is 4. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-04-01 to 2025-04-01.)
ArticleCitations
Lightweight Dynamic Redundancy Control with Adaptive Encoding for Server-based Storage108
WALSH: Write-Aggregating Log-Structured Hashing for Hybrid Memory45
From Missteps to Milestones: A Journey to Practical Fail-Slow Detection39
Localized Validation Accelerates Distributed Transactions on Disaggregated Persistent Memory34
Introduction to the Special Section on USENIX ATC 202319
Lightweight Robust Size Aware Cache Management16
Bridging Software-Hardware for CXL Memory Disaggregation in Billion-Scale Nearest Neighbor Search16
Derrick: A Three-layer Balancer for Self-managed Continuous Scalability16
Repair Pipelining for Erasure-coded Storage: Algorithms and Evaluation15
Survey of Distributed File System Design Choices15
Hybrid Block Storage for Efficient Cloud Volume Service14
Reprogramming 3D TLC Flash Memory based Solid State Drives14
A Dynamic Characteristic Aware Index Structure Optimized for Real-world Datasets13
eZNS: Elastic Zoned Namespace for Enhanced Performance Isolation and Device Utilization13
Understanding Persistent-memory-related Issues in the Linux Kernel13
Two Reconfigurable NDP Servers: Understanding the Impact of Near-Data Processing on Data Center Applications12
IS-HBase: An In-Storage Computing Optimized HBase with I/O Offloading and Self-Adaptive Caching in Compute-Storage Disaggregated Infrastructure11
Perseid: A Secondary Indexing Mechanism for LSM-Based Storage Systems9
Project Silica: Towards Sustainable Cloud Archival Storage in Glass9
Extending and Programming the NVMe I/O Determinism Interface for Flash Arrays9
Introduction to the Special Section on USENIX ATC 20229
Exploiting Flat Namespace to Improve File System Metadata Performance on Ultra-Fast, Byte-Addressable NVMs9
Holographic Storage for the Cloud: advances and challenges9
Power-optimized Deployment of Key-value Stores Using Storage Class Memory8
An In-depth Comparative Analysis of Cloud Block Storage Workloads: Findings and Implications8
Pattern-Based Prefetching with Adaptive Cache Management Inside of Solid-State Drives8
ctFS: Replacing File Indexing with Hardware Memory Translation through Contiguous File Allocation for Persistent Memory7
Introduction to the Special Section on USENIX FAST 20247
HM-ORAM: A Lightweight Crash-consistent ORAM Framework on Hybrid Memory System7
HLN-Tree: A memory-efficient B+-Tree with huge leaf nodes and locality predictors6
A Large-scale Analysis of Hundreds of In-memory Key-value Cache Clusters at Twitter6
Simplicity as the Ultimate Principle: The Art of Garbage Collection Management in SSDs Inspired by Natural Data Behavior6
Tunable Encrypted Deduplication with Attack-resilient Key Management6
The Past, Present, and Future of Storage Technologies (Part 1 of 2)6
Multi-objective Optimization of Data Placement in a Storage-as-a-Service Federated Cloud6
gLSM: Using GPGPU to Accelerate Compactions in LSM-tree-based Key-value Stores5
The Concurrent Learned Indexes for Multicore Data Storage5
Characterization Summary of Performance, Reliability, and Threshold Voltage Distribution of 3D Charge-Trap NAND Flash Memory5
GoSeed: Optimal Seeding Plan for Deduplicated Storage4
A Universal SMR-aware Cache Framework with Deep Optimization for DM-SMR and HM-SMR Disks4
Index Shipping for Efficient Replication in LSM Key-Value Stores with Hybrid KV Placement4
Empowering Storage Systems Research with NVMeVirt: A Comprehensive NVMe Device Emulator4
Fastmove: A Comprehensive Study of On-Chip DMA and its Demonstration for Accelerating Data Movement in NVM-based Storage Systems4
Programming Abstractions for Managing Workflows on Tiered Storage Systems4
Twizzler: A Data-centric OS for Non-volatile Memory4
Reliability Evaluation of Erasure-coded Storage Systems with Latent Errors4
A Disk Failure Prediction Method Based on Active Semi-supervised Learning4
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