VM aware journaling: improving journaling file system performance in virtualization environments

Huang, Ting-Chang; Chang, Da-Wei

doi:10.1002/spe.1069

Cited by 6 publications

(3 citation statements)

References 35 publications

(27 reference statements)

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“…Additionally, the journaling of both data and metadata is considered impractical due to the performance degradation [Le et al 2012]. As one solution to the performance problem of data journaling, it was recently proposed to maintain the journals of multiple virtual machines in the main memory of the host, presuming that the hardware and virtual machine monitor are sufficiently reliable [Huang and Chang 2011].…”

Section: Discussionmentioning

confidence: 99%

Improving Bandwidth Efficiency for Consistent Multistream Storage

Hatzieleftheriou

Anastasiadis

2013

ACM Trans. Storage

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Synchronous small writes play a critical role in system availability because they safely log recent state modifications for fast recovery from crashes. Demanding systems typically dedicate separate devices to logging for adequate performance during normal operation and redundancy during state reconstruction. However, storage stacks enforce page-sized granularity in data transfers from memory to disk. Thus, they consume excessive storage bandwidth to handle small writes, which hurts performance. The problem becomes worse, as filesystems often handle multiple concurrent streams, which effectively generate random I/O traffic. In a journaled filesystem, we introduce wasteless journaling as a mount mode that coalesces synchronous concurrent small writes of data into full page-sized journal blocks. Additionally, we propose selective journaling to automatically activate wasteless journaling on data writes with size below a fixed threshold. We implemented a functional prototype of our design over a widely-used filesystem. Our modes are compared against existing methods using microbenchmarks and application-level workloads on stand-alone servers and a multitier networked system. We examine synchronous and asynchronous writes. Coalescing small data updates to the journal sequentially preserves filesystem consistency while it reduces consumed bandwidth up to several factors, decreases recovery time up to 22%, and lowers write latency up to orders of magnitude.

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Section: Discussionmentioning

confidence: 99%

Improving Bandwidth Efficiency for Consistent Multistream Storage

Hatzieleftheriou

Anastasiadis

2013

ACM Trans. Storage

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“…Data evictions also need to be logged because they involve multiple storage devices. As in existing journaling approaches , the logging is performed in transactions. To effectively leverage the parallelism between the flash memory and disk devices, a separate journal space is allocated on each device, and the logging (i.e., writing of the journal data) is performed on the basis of the distribution algorithm shown in Figure .…”

Section: Discussionmentioning

confidence: 99%

TridentFS: a hybrid file system for non-volatile RAM, flash memory and magnetic disk

Huang

Chang

2014

Softw. Pract. Exper.

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SUMMARYA 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%.

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“…The SDFS does not require extra labels from the applications, because the SDFS provides tenants with guarantees through allocating resources at per‐image‐file granularity. VMA aims to improve system performance by eliminating journal writes through placing the journal area in the VMM memory rather than on the disk, but it cannot handle the interference caused by delayed write‐back. By contrast, the SDFS can provide VMs with predictable performance by taking into account three file system characteristics, namely, delayed write‐back, journaling, and caching.…”

Section: Related Workmentioning

confidence: 99%

SDFS: A software‐defined file system for multitenant cloud storage

et al. 2018

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Performance isolation is highly desirable in cloud platforms where the virtual disks of virtual machines are simply large files on the shared and networked storage servers. However, existing isolation techniques cannot deal with the implications of the file system used by the networked storage servers, such that underlying resource usage is unpredictable (eg, the delayed write-back mechanism could postpone writes, and the journaling mechanism could amplify writes). The lack of visibility on underlying resource usage leads to the predicament of being unable to meet isolation goals. In this paper, we present a software-defined file system (SDFS) that exploits the underlying file system to allocate resources at per-image-file granularity and provide tenants with guaranteed throughput. The SDFS comprises two components: control plane and data plane. At the control plane, we provide a set of system calls to document tenant performance requirements into the metadata of image files. At the data plane, we construct a file-based scheduler to manage memory and disk resources according to the tenant performance requirements. The SDFS design does not require a modification to guest operating systems, hypervisors, or file server protocols. Through a prototype implementation, we demonstrate that the SDFS can meet isolation goals and increase resource utilization with negligible overhead.

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VM aware journaling: improving journaling file system performance in virtualization environments

Cited by 6 publications

References 35 publications

Improving Bandwidth Efficiency for Consistent Multistream Storage

Improving Bandwidth Efficiency for Consistent Multistream Storage

TridentFS: a hybrid file system for non-volatile RAM, flash memory and magnetic disk

SDFS: A software‐defined file system for multitenant cloud storage

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