TridentFS: a hybrid file system for non‐volatile RAM, flash memory and magnetic disk. (19th November 2014)

• Record Type: Journal Article
• Authors: Huang, Ting‐Chang; Chang, Da‐Wei
• Is Part Of: Software, practice & experience. Volume 46:Number 3(2016)
• Page Start: 291
• Page End: 318
• Publication Date: 2014-11-19
• Subjects: hybrid file systems -- non‐volatile memory -- flash memory -- magnetic disk -- file distribution; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.2299
• Languages: English
• ISSNs: 0038-0644

Abstract

Summary: A hybrid file system with high flexibility and performance, called Trident file system (TridentFS), is proposed to manage three types of storage with different performance characteristics, that is, Non‐Volatile RAM (NVRAM), flash memory and magnetic disk. Unlike previous NVRAM‐based hybrid file systems, novel techniques are used in TridentFS to improve the flexibility and performance. TridentFS is flexible by the support of various forms of flash memory and a wide range of NVRAM size. The former is achieved on the basis of the concept of stackable file systems, and the latter is achieved by allowing data eviction from the NVRAM. TridentFS achieves high performance by keeping hot data in the NVRAM and allowing data evicted from the NVRAM to be parallel distributed to the flash memory and disk. A data eviction policy is proposed to determine the data to be evicted from the NVRAM. Moreover, a data distribution algorithm is proposed to effectively leverage the parallelism between flash memory and disk during data distribution. TridentFS is implemented as a loadable module on Linux 2.6.29. The performance results show that it works well for both small‐sized and large‐sized NVRAM, and the proposed eviction policy outperforms LRU by 27%. Moreover, by effectively leveraging the parallelism between flash memory and disk, the proposed data distribution algorithm outperforms the RAID‐0 and a size‐based distribution method by up to 471.6% and 82.6%, respectively. By considering the data size and performance characteristics of the storage, the proposed data distribution algorithm outperforms the greedy algorithm by up to 15.5%. Copyright © 2014 John Wiley & Sons, Ltd.