Zhichao Cao, Hao Wen, University of Minnesota; Xiongzi Ge, NetApp; Jingwei Ma, Nankai University; Jim Diehl, David H. C. Du; University of Minnesota
ACM Transactions on Storage (TOS)
Volume 15 Issue 1, March 2019
With the rapid increase in the amount of data produced and the development of new types of storage devices, storage tiering continues to be a popular way to achieve a good tradeoff between performance and cost-effectiveness. In a basic two-tier storage system, a storage tier with higher performance and typically higher cost (the fast tier) is used to store frequently-accessed (active) data while a large amount of less-active data are stored in the lower-performance and low-cost tier (the slow tier). Data are migrated between these two tiers according to their activity. In this article, we propose a Tier-aware Data Deduplication-based File System, called TDDFS, which can operate efficiently on top of a two-tier storage environment.
Specifically, to achieve better performance, nearly all file operations are performed in the fast tier. To achieve higher cost-effectiveness, files are migrated from the fast tier to the slow tier if they are no longer active, and this migration is done with data deduplication. The distinctiveness of our design is that it maintains the non-redundant (unique) chunks produced by data deduplication in both tiers if possible. When a file is reloaded (called a reloaded file) from the slow tier to the fast tier, if some data chunks of the file already exist in the fast tier, then the data migration of these chunks from the slow tier can be avoided. Our evaluation shows that TDDFS achieves close to the best overall performance among various file-tiering designs for two-tier storage systems.
Haryadi S. Gunawi and Riza O. Suminto, University of Chicago; Russell Sears and Casey Golliher, Pure Storage; Swaminathan Sundararaman, Parallel Machines; Xing Lin and Tim Emami, NetApp; Weiguang Sheng and Nematollah Bidokhti, Huawei; Caitie McCaffrey, Twitter; Gary Grider and Parks M. Fields, Los Alamos National Laboratory; Kevin Harms and Robert B. Ross, Argonne National Laboratory; Andree Jacobson, New Mexico Consortium; Robert Ricci and Kirk Webb, University of Utah; Peter Alvaro, University of California, Santa Cruz, Mingzhe Hao, Huaicheng Li, and H. Birali Runesha, University of Chicago
ACM Transactions on Storage (TOS) TOS
Volume 14 Issue 3, October 2018
Article No. 23
Fail-slow hardware is an under-studied failure mode. We present a study of 114 reports of fail-slow hardware incidents, collected from large-scale cluster deployments in 14 institutions. We show that all hardware types such as disk, SSD, CPU, memory, and network components can exhibit performance faults. We made several important observations such as faults convert from one form to another, the cascading root causes and impacts can be long, and fail-slow faults can have varying symptoms. From this study, we make suggestions to vendors, operators, and systems designers.
Ram Kesavan, Rohit Singh, Travis Grusecki, NetApp Inc. Yuvraj Patel, University of Wisconsin-Madison
ACM Transactions on Storage (TOS)
Volume 13 Issue 3, September 2017
Article No. 23
NetApp®WAFL® is a transactional file system that uses the copy-on-write mechanism to support fast write performance and efficient snapshot creation. However, copy-on-write increases the demand on the file system to find free blocks quickly, which makes rapid free space reclamation essential. Inability to find free blocks quickly may impede allocations for incoming writes. Efficiency is also important, because the task of reclaiming free space may consume CPU and other resources at the expense of client operations. In this article, we describe the evolution (over more than a decade) of the WAFL algorithms and data structures for reclaiming space with minimal impact to the overall performance of the storage appliance.
Mark W. Storer, Kevin M. Greenan, Ethan L. Miller, and Kaladhar Voruganti.
POTSHARDS is an archival storage system that provides long-term recoverable security for data with very long lifetimes by using provably secure secret splitting.
Users are storing ever-increasing amounts of information digitally, driven by many factors including government regulations and the public’s desire to digitally record their personal histories. Unfortunately, many of the security mechanisms that modern systems rely upon, such as encryption, are poorly suited for storing data for indefinitely long periods of time; it is very difficult to manage keys and update cryptosystems to provide secrecy through encryption over periods of decades. Worse, an adversary who can compromise an archive need only wait for cryptanalysis techniques to catch up to the encryption algorithm used at the time of the compromise in order to obtain “secure” data. To address these concerns, we have developed POTSHARDS, an archival storage system that provides long-term security for data with very long lifetimes without using encryption. Secrecy is achieved by using unconditionally secure secret splitting and spreading the resulting shares across separately managed archives. Providing availability and data recovery in such a system can be difficult; thus, we use a new technique, approximate pointers, in conjunction with secure distributed RAID techniques to provide availability and reliability across independent archives. To validate our design, we developed a prototype POTSHARDS implementation. In addition to providing us with an experimental testbed, this prototype helped us to understand the design issues that must be addressed in order to maximize security.
In ACM Transactions on Storage (TOS), Vol. 5, No. 2, June 2009, Article No. 5