Frog: A Framework for Context-Based File Systems
Accelerating File System Metadata Access with Byte-addressable Non-Volatile Memory
SWANS: An Inter-Disk Wear-Leveling Strategy for RAID-0 Structured SSD Arrays
Shuffle Index: Efficient and Private Access to Outsourced Data
Does RAID Improve Lifetime of SSD Arrays?
ImmortalGraph: A System for Storage and Analysis of Temporal Graphs
On the Trade-Offs among Performance, Energy, and Endurance in a Versatile Hybrid Drive
Improving Flash-based Disk Cache with Lazy Adaptive Replacement
Statistical Techniques to Identify Predictive Groupings in Storage System Accesses
For years the increasing popularity of flash memory has been changing storage systems. Flash-based solid state drives(SSD) are widely used as a new cache tier on top of hard disk drives(HDD) to speed up data intensive applications. However, the endurance problem of flash memory remains a concern and is getting worse with the adoption of MLC and TLC flash. In this paper, we propose a novel cache management algorithm for flash-based disk cache, named Lazy Adaptive Replacement Cache(LARC). LARC adopts the idea of selective caching to filter out seldom accessed blocks and prevent them from entering cache. This avoids cache pollution and preserves popular blocks in cache for a longer period of time, leading to higher hit rate. Meanwhile, by avoiding unnecessary cache replacements, LARC reduces the volume of data written to SSD and yields an SSD friendly access pattern. In this way, LARC improves the performance and endurance of SSD at the same time. LARC is self-tuning and low-overhead. It has been extensively evaluated by both trace-driven simulations and synthetic benchmarks on a prototype implementation. Our experiments show that LARC outperforms state-of-art algorithms for different kinds of workloads and extends SSD lifetime by up to 15.7 times.