ACM Transactions on

Storage (TOS)

Latest Articles

Skylight—A Window on Shingled Disk Operation

We introduce Skylight, a novel methodology that combines software and hardware techniques to reverse engineer key properties of drive-managed Shingled... (more)


Modern storage systems orchestrate a group of disks to achieve their performance and reliability goals. Even though such systems are designed to withstand the failure of individual disks, failure of multiple disks poses a unique set of challenges. We empirically investigate disk failure data from a large number of production systems, specifically... (more)


The Bϵ-tree File System, or BetrFS (pronounced “better eff ess”), is the first in-kernel file system to use a write-optimized data structure (WODS). WODS are promising building blocks for storage systems because they support both microwrites and large scans efficiently. Previous WODS-based file systems have shown promise but have been hampered in several ways, which BetrFS... (more)

Shuffle Index

Data outsourcing and cloud computing have been emerging at an ever-growing rate as successful approaches for allowing users and companies to rely on external services for storing and managing data. As data and access to them are not under the control of the data owner, there is a clear need to provide proper confidentiality protection. Such... (more)


Note from Editor-in-Chief

I am delighted to announce that ACM Transactions on Storage is now being indexed by Thomson-Reuters through the Science Citation Index Expanded (SciSearch), Journal Citation Reports/Science Edition, Current Contents/Engineering Computing and Technology. This is in recognition of the quality of the articles appearing in Transactions on Storage, and I would like to extend my gratitude and appreciation to all of authors who have made this possible. As the old adage says, "a rising tide raises all boats" and the increased visibility of Transactions on Storage increases the impact of your article, and will attract even higher quality articles to our journal.

I want to again thank all of the authors who have made this possible, and express my hope that the growing impact of Transactions on Storage will continue. Computer Science is now a mature discipline, and the importance of journal publication is increasing. By sending your best work to Transactions on Storage you contribute to the field and to the standing of this journal.

New options for ACM authors to manage rights and permissions for their work

ACM introduces a new publishing license agreement, an updated copyright transfer agreement, and a new author-pays option which allows for perpetual open access through the ACM Digital Library. For more information, visit the ACM Author Rights webpage.

Forthcoming Articles

H-Scale: A Fast Approach to Scale Disk Arrays via Hybrid Stripe Deployment

Statistical Techniques to Identify Predictive Groupings in Storage System Accesses

SWANS: An Inter-Disk Wear-Leveling Strategy for RAID-0 Structured SSD Arrays

Does RAID Improve Lifetime of SSD Arrays?

MultiLanes: Providing Virtualized Storage for OS-level Virtualization on Many Cores

OS-level virtualization is an efficient method for server consolidation. However, the sharing of kernel services among the co-located virtualized environments (VEs) incurs performance interference between each other. Especially, interference effects within the shared I/O stack would lead to severe performance degradations on many-core platforms incorporating fast storage technologies (e.g., non-volatile memories). This article presents MultiLanes, a virtualized storage system for OS-level virtualization on many cores. MultiLanes builds an isolated I/O stack on top of a virtualized storage device for each VE to eliminate contention on kernel data structures and locks between them, thus scaling them to many cores. Moreover, the overhead of storage device virtualization is tuned to be negligible so that MultiLanes can deliver competitive performance against Linux. Apart from scalability, MultiLanes also delivers flexibility and security to all the VEs, as the virtualized storage device allows each VE to run its own guest file system. The evaluation of our prototype system built for Linux container (LXC) on a 32-core machine with both a RAM disk and a flash-based SSD demonstrates MultiLanes scales much better than Linux in micro- and macro-benchmarks, bringing significant performance improvements.

Improving Flash-based Disk Cache with Lazy Adaptive Replacement

Efficient Memory-mapped I/O on Fast Storage Device

In operating systems, memory-mapped I/O (mmio) is an important access method that maps data to a memory. When mmio is used, hot data reside in the memory and clod data do in storage device, and data placement depends on the virtual memory subsystem of the operating system. Since the performance of storage has a direct impact on the performance of mmio, it is widely expected that better storage will lead to better performance. However, the expectation is limited when fast storage is used because the virtual memory subsystem does not reflect the feature of fast storage. In this article, we examine the mmio path to determine the influence of fast storage. We find that the overhead of the virtual memory subsystem, negligible on the HDD, prevents applications from using the full performance of fast storage. We present several optimization techniques and modify the Linux kernel to implement those techniques. Experimental results show that our optimized mmio has up to 7x better performance that the original. Compared with a system that has enough memory to keep all data, we achieve 92% performance of the resource-rich system. This implies that our system can effectively extend the main memory with fast storage.

LoneStar RAID: Massive Array of Offline Disks for Archival Systems

Storage Workload Identification

Workload identification is an important problem for cloud providers to solve because 1) providers can leverage this information to co-locate similar workloads in order to make the system more predictable 2) providers can identify workloads and subsequently give guidance to the subscribers as to associated best practices for provisioning those workloads. Historically, people have identified workloads by looking at their read/write ratios, random/sequential ratios, block size and inter-arrival frequency. Researchers are aware that workload characteristics change over time and that one cannot just take a point in time view of a workload because that will incorrectly characterize workload behavior. Increasingly, manual detection of workload signature is becoming harder because 1) it is difficult for a human to detect a pattern, and 2) representing a workload signature by a tuple consisting of {\it average} values for each of the signature components leads to a large error. In this paper, we present workload signature detection and matching algorithm that is able to correctly identify workload signatures and match them with other similar workload signatures. We have tested our algorithm on nine different workloads generated using publicly available traces and on real customer workloads running in field to show robustness of our approach.

TrueErase: Leveraging an Auxiliary Data Path for Per-file Secure Deletion

One important aspect of privacy is the ability to securely delete sensitive data from electronic storage in such a way that it cannot be recovered; we call this action secure deletion. Short of physically destroying the entire storage medium, existing system-based secure-deletion solutions tend to be piecemeal at best  they may only work for one type of storage or file system, may force the user to delete all files instead of selected ones, may require the added complexities of encryption and key storage, may require extensive changes and additions to the computers operating system or storage firmware, and may not handle system crashes gracefully. NAND flash storage is particularly troublesome, because its storage firmware makes it nearly impossible for the operating system to securely delete files and/or verify that the files have indeed been erased. We present TrueErase, a holistic secure-deletion framework suitable for individual systems that contain sensitive data. Through its design, implementation, verification, and evaluation on both a hard drive and NAND flash, TrueErase shows that it is possible to construct a per-file, encryption-free, secure-deletion framework that can accommodate different storage media and legacy file systems, require limited changes to legacy systems, and handle common crash scenarios.

Internal Parallelism of Flash Memory based Solid State Drives

Flash memory based solid state drives (SSDs) have shown a great potential to change todays storage infrastructure fundamentally. A unique merit of an SSD is its internal parallelism. In this paper we present a comprehensive study on understanding and exploiting internal parallelism of SSDs for high-speed data processing. Through extensive experiments and thorough analysis, we find that exploiting internal parallelism can not only substantially improve I/O performance (e.g., 7.2x) but also lead to many surprising side effects and dynamics, which have a strong implication to system and application designers. Based on these findings, we also present a set of case studies in database management systems, a typical data-intensive application, and show that exploiting internal parallelism can substantially improve system performance, and in the meantime, it also changes the equation for optimizing application performance and calls for a careful reconsideration on various design choices.

Efficient Dynamic Provable Possession of Remote Data via Update Trees

Storage Workload Identification

A User-Friendly Log Viewer for Storage Systems

For customers with remote support, the system collects and transmits logs to a central enterprise repository, where these are monitored for alerts, problem forecasting and troubleshooting. Very large log files limit the interpretability for the support engineers. For an engineer, a large volume of log messages may not pose any problem. Often it is desired to present the log messages in a comprehensive manner where a person can view the important messages first and then go into details if required. In this paper, we present a user-friendly log viewer where we first hide the unimportant messages from the log file. Messages with low utility are considered inconsequential as their removal does not impact the end user for the aforesaid purpose such as problem forecasting or troubleshooting. We relate the utility of a message to the probability of its appearance in the due context. We present machine learning based techniques that computes the usefulness of individual messages in a log file. (30% to 55%), with minimal error rates ( 7% to 20%). When limited user feedback is available, we show modifications to the technique to learn the user intent and accordingly further reduce the error.


Publication Years 2005-2015
Publication Count 180
Citation Count 1102
Available for Download 180
Downloads (6 weeks) 1371
Downloads (12 Months) 15181
Downloads (cumulative) 122610
Average downloads per article 681
Average citations per article 6
First Name Last Name Award
Sarita Adve ACM Fellows (2010)
Emery David Berger ACM Senior Member (2010)
Alok Choudhary ACM Fellows (2009)
Deborah Estrin ACM-W Athena Lecturer Award (2006)
ACM Fellows (2000)
Gregory Ganger ACM Distinguished Member (2007)
Garth A Gibson ACM Fellows (2012)
ACM Doctoral Dissertation Award (1991)
Ramesh Govindan ACM Fellows (2011)
John Heidemann ACM Senior Member (2007)
Kai Li ACM Fellows (1998)
Ming Li ACM Fellows (2006)
Mingqiang Li ACM Fellows (2006)
Ethan L Miller ACM Distinguished Member (2013)
Walid Najjar ACM Distinguished Member (2015)
ACM Senior Member (2014)
Michael Reiter ACM Fellows (2008)
Stefan Savage ACM Fellows (2010)
Steven Scott ACM Fellows (2012)
Kenneth C Sevcik ACM Fellows (1997)
Anand Sivasubramaniam ACM Distinguished Member (2010)
ACM Senior Member (2009)
Chandramohan A Thekkath ACM Fellows (2009)
Gene Tsudik ACM Fellows (2014)
ACM Senior Member (2013)
Amin Vahdat ACM Fellows (2011)
David Wagner ACM Doctoral Dissertation Award (2001)
Randy Wang ACM Eugene L. Lawler Award for Humanitarian Contributions within Computer Science and Informatics (2007)
Marianne Winslett ACM Fellows (2006)
Tao Xie ACM Distinguished Member (2015)
ACM Senior Member (2011)
Philip S Yu ACM Fellows (1997)
Yuanyuan Zhou ACM Fellows (2013)
ACM Distinguished Member (2011)
Yuanyuan Zhou ACM Fellows (2013)
ACM Distinguished Member (2011)

First Name Last Name Paper Counts
Andrea Arpaci-Dusseau 9
Youjip Won 6
Teiwei Kuo 6
Erez Zadok 6
Remzi Arpaci-Dusseau 5
Raju Rangaswami 4
Bianca Schroeder 4
Remzi Arpaci-Dusseau 4
Charles Wright 4
Randal Burns 4
Weimin Zheng 4
Xiao Qin 4
Ethan Miller 4
Lidong Zhou 3
Hyeonsang Eom 3
Youngjin Yu 3
Hong Jiang 3
Darrell Long 3
Stergios Anastasiadis 3
James Cipar 3
Song Jiang 3
Yuanhao Chang 3
Jenwei Hsieh 3
Jiwu Shu 3
Vijayan Prabhakaran 3
Guangyan Zhang 3
Lipin Chang 3
Ilias Iliadis 3
Heonyoung Yeom 3
Yuanyuan Zhou 3
Narasimha Reddy 3
Hyokyung Bahn 3
Nitin Agrawal 3
Ohad Rodeh 3
Dan Feng 3
John MacCormick 2
Zhenmin Li 2
Peter Desnoyers 2
Swaminathan Sundararaman 2
Sriram Subramanian 2
Dongin Shin 2
Bo Mao 2
Lei Tian 2
Patrick Lee 2
Gregory Ganger 2
Cheng Chen 2
Jeffrey Chase 2
Tao Xie 2
Roger Zimmermann 2
Erik Riedel 2
Jaemin Jung 2
Eunji Lee 2
Scott Brandt 2
Wei Xue 2
Evangelos Eleftheriou 2
Xiaoyu Hu 2
Kiran Muniswamy-Reddy 2
Nikolai Joukov 2
Chinhsien Wu 2
Ashvin Goel 2
Mark Storer 2
Suzhen Wu 2
Shu Yin 2
Gopalan Sivathanu 2
Alma Riska 2
Daniel Fryer 2
Angela Brown 2
Arkady Kanevsky 2
Qingsong Wei 2
Mario Blaum 2
Adam Manzanares 2
William Bolosky 2
Gene Tsudik 2
Bo Hong 2
Anand Sivasubramaniam 2
An Wang 2
Xiaoning Ding 2
Yuehai Xu 2
Sudhanva Gurumurthi 2
Jianxi Chen 2
Ali Tosun 2
Xiaojun Ruan 2
Jongmin Gim 2
Peter Reiher 2
Geoff Kuenning 2
Eitan Bachmat 2
Taeho Hwang 2
Kyuho Park 2
Amanpreet Mukker 1
Leo Arulraj 1
Einar Mykletun 1
Mahesh Balakrishnan 1
Weikeng Liao 1
Walid Najjar 1
Deepak Bobbarjung 1
Josef Bacik 1
Seokhei Cho 1
Sooyong Kang 1
Pieter Hartel 1
Windsor Hsu 1
John Heidemann 1
Xiaodong Li 1
Kimberly Keeton 1
Phillipa Gill 1
Ricardo Koller 1
Lingfang Zeng 1
Chandramohan Thekkath 1
Kirsten Hildrum 1
Philip Yu 1
Seonho Kim 1
Ron Arnan 1
Kaushik Veeraraghavan 1
Zhen Huang 1
Eno Thereska 1
Hyojun Kim 1
Lakshmi Bairavasundaram 1
David Wagner 1
Dilma Silva 1
Ahmed Amer 1
Haifeng Yu 1
Venugopalan Ramasubramanian 1
James Plank 1
Jin Li 1
Lawrence Chiu 1
Lianghong Xu 1
Mary Baker 1
Dinh Tran 1
Joseph Murray 1
Armando Fox 1
Andrew Huang 1
Feng Chen 1
Ming Li 1
Lei Tian 1
Jon Elerath 1
Jiri Schindler 1
Gyudong Shim 1
Youngwoo Park 1
Qiang Cao 1
Shan Lu 1
Seungwon Hwang 1
Navendu Jain 1
Lawrence You 1
Zachary Peterson 1
Mark Shaw 1
Xianghong Luo 1
Yan Li 1
Kai Li 1
Hyungju Cho 1
Taesun Chung 1
Rob Johnson 1
Donald Porter 1
Amogh Akshintala 1
Sara Foresti 1
Pierangela Samarati 1
Ming Wu 1
Wenguang Chen 1
Mohammed Alghamdi 1
Matthew Curry 1
Michael Swift 1
Garth Gibson 1
Emery Berger 1
Jacob Lorch 1
Maithili Narasimha 1
Yang Wang 1
Chris Mason 1
Sam Noh 1
Vincent Freeh 1
Nandan Tammineedi 1
Mathew Oldham 1
Rick Coulson 1
Tsungtai Yeh 1
Eunki Kim 1
Radu Sion 1
Anton Kos 1
Veljko Milutinovic 1
Xiao Qin 1
Nguyen Tran 1
Frank Chiang 1
Yulai Xie 1
Kanchi Gopinath 1
Michael Bender 1
Abutalib Aghayev 1
Kaiwei Li 1
Asim Kadav 1
Xiaosong Ma 1
Stephen Scott 1
Hyungkyu Chang 1
Sukwoo Kang 1
Sheng Qiu 1
Soyoon Lee 1
Sanjeev Trika 1
Debra Hensgen 1
Haim Helman 1
Tsansheng Hsu 1
Weikuan Shih 1
Mark Huang 1
Vasily Tarasov 1
Edmund Nightingale 1
Picheng Hsiu 1
Rohit Jain 1
Joel Wolf 1
Kevin Harms 1
William Allcock 1
Yubiao Pan 1
Ernst Biersack 1
Clement Dickey 1
Phung Huynh 1
Amin Vahdat 1
Changxun Wu 1
Weihang Jiang 1
Aichun Pang 1
Junfeng Yang 1
Hyunjin Choi 1
Jaewoo Choi 1
Ningfang Mi 1
Vagelis Hristidis 1
Cheng Huang 1
Gaewon You 1
Jasna Milovanovic 1
Pochun Huang 1
Jaka Sodnik 1
Angelos Bilas 1
Kevin Bowers 1
Guanying Wu 1
Xubin He 1
Ben Eckart 1
Sajib Kundu 1
Christos Karamanolis 1
Magnus Karlsson 1
Thomas Schwarz 1
Harikesavan Krishnan 1
Jason Flinn 1
Robert Latham 1
Robert Ross 1
John Lui 1
Yuxing Peng 1
Xuechen Zhang 1
Alexey Tumanov 1
Jack Sun 1
Dushyanth Narayanan 1
Edward Chang 1
Chris Dragga 1
Marianne Winslett 1
James Lentini 1
Anxiao(Andrew) Jiang 1
Nitin Garg 1
Garth Gibson 1
Darrell Long 1
Bruno Quaresma 1
Phaneendra Reddy 1
Ming Chen 1
Ji Zhang 1
Alexander Thomasian 1
Ivan Popov 1
Luis Bathen 1
Binny Gill 1
Aydan Yumerefendi 1
Masaaki Tanaka 1
Ying Lin 1
Jaemin Ryu 1
Yongdai Kim 1
Gerald Popek 1
Demetrios Zeinalipour-Yazti 1
Song Lin 1
Assaf Natanzon 1
Xiaojian Wu 1
John Garrison 1
TingHao Cheng 1
Sara Stancin 1
Jianzhong Huang 1
Jinyang Li 1
Jiwu Shu 1
Bradley Kuszmaul 1
Fan Yang 1
Weishinn Ku 1
Lee Ward 1
Dahlia Malkhi 1
Junseok Shim 1
Gokhan Memik 1
Cezary Dubnicki 1
Kei Davis 1
Jianhong Lin 1
Jonathan Strickland 1
Jin Qian 1
Avishay Traeger 1
Sungroh Yoon 1
Tsengyi Chen 1
Shaun Benjamin 1
Ian Adams 1
Chunghsien Wu 1
Geming Chiu 1
Lars Bongo 1
Sugata Ghosal 1
Kristof Roomp 1
Lisa Fleischer 1
Hong Zhu 1
Ruben Michel 1
Philip Carns 1
Charles Bacon 1
Runhui Li 1
Michael Kozuch 1
Austin Donnelly 1
Dan Tsafrir 1
Ajay Dholakia 1
Zoran Dimitrijević 1
Klaus Schauser 1
Chongfeng Hu 1
Nick Murphy 1
Dongin Shin 1
Evgenia Smirni 1
Kaladhar Voruganti 1
Ao Ma 1
Lanyue Lu 1
Chunho Ng 1
Ragib Hasan 1
David Holland 1
Tyler Simon 1
Knut Grimsrud 1
Kuoyi Huang 1
Byeonggil Jeon 1
Philip Shilane 1
Grant Wallace 1
Kuei Sun 1
Hyojun Kim 1
Cristian Ungureanu 1
Deborah Estrin 1
Thanos Makatos 1
William Josephson 1
Brian Noble 1
Sotirios Damouras 1
Xiaoyun Zhu 1
Jay Dave 1
Kaushik Dutta 1
Nitin Gupta 1
Garth Goodson 1
David Essary 1
Yongchiang Tay 1
James Megquier 1
Seungho Lim 1
Bradley Vander Zanden 1
Mingdi Xue 1
Jun Yang 1
Minghua Chen 1
Zhifeng Chen 1
Michael Abd-El-Malek 1
Michael Reiter 1
Andromachi Hatzieleftheriou 1
William Jannen 1
Yizheng Jiao 1
Youshan Miao 1
Alberto Miranda 1
Sascha Effert 1
André Brinkmann 1
Mohit Saxena 1
Vana Kalogeraki 1
Di Ma 1
Vinodh Venkatesan 1
David Chambliss 1
Deepak Ganesan 1
Ramesh Govindan 1
Yannis Klonatos 1
Manolis Marazakis 1
David Flynn 1
Michael Vrable 1
Geoffrey Voelker 1
Alexandros Batsakis 1
Yungfeng Lu 1
Sašo Tomažič 1
Sriram Sankar 1
Keqin Li 1
Alysson Bessani 1
Miguel Correia 1
Randolph Wang 1
Mansour Shafaei 1
Gerardo Pelosi 1
Enhong Chen 1
Zhichao Li 1
Yao Sun 1
Yangwook Kang 1
Tom Friedetzky 1
Toni Cortes 1
Zhiwei Sun 1
Anthony Skjellum 1
Satoshi Sugahara 1
Rakesh Iyer 1
Jian Zhang 1
Mahmut Kandemir 1
Dimitrios Gunopulos 1
Suresh Jagannathan 1
Jeanna Matthews 1
Krishna Kant 1
Jongmoo Choi 1
Hsinwen Wei 1
Mohammed Khatib 1
Hyungjong Shin 1
Rahat Mahmood 1
Sarita Adve 1
Michail Flouris 1
Priya Sehgal 1
Kai Li 1
Abhishek Rajimwale 1
Chengkang Hsieh 1
Fred Douglis 1
Akshay Katta 1
Michael Stumm 1
David Quigley 1
Puja Gupta 1
Michael Swift 1
Samuel Lang 1
Jianqiang Luo 1
Alina Oprea 1
Lihao Xu 1
Marcus Jager 1
Ryan Peterson 1
Kenneth Sevcik 1
Feng Wang 1
Mohammad Zubair 1
Yinlong Xu 1
Qian Chang 1
Elie Krevat 1
Kahwai Lee 1
Tomer Hertz 1
KK Rao 1
Richard Spillane 1
Anthony Tung 1
Chihyuan Huang 1
Hong Jiang 1
Yinjin Fu 1
Qin Xin 1
James Plank 1
Sam Noh 1
Peter Trifonov 1
Yankit Li 1
Thomas Talpey 1
PingYi Hsu 1
Muthian Sivathanu 1
Sumeet Sobti 1
Junwen Lai 1
Fenghao Zhang 1
Nihat Altiparmak 1
Kushagra Vaid 1
Martín Farach-Colton 1
Arvind Krishnamurthy 1
Sejin Kwon 1
Leif Walsh 1
Ankur Mittal 1
Prashant Pandey 1
Stefano Paraboschi 1
Wentao Han 1
Xunfei Jiang 1
Mark Corner 1
John Douceur 1
Nitin Agrawal 1
Yupu Zhang 1
Dutch Meyer 1
Sudharshan Vazhkudai 1
Qian Wang 1
Alok Choudhary 1
Mais Nijim 1
Charles Weddle 1
Changhyun Park 1
Jaehyuk Cha 1
Ben Greenstein 1
Beomjoo Seo 1
Akshat Verma 1
Taokai Lam 1
Mingqiang Li 1
Sangeetha Seshadri 1
Mike Qin 1
Antony Rowstron 1
Jai Menon 1
Gordon Hughes 1
Rajiv Wickremesinghe 1
Liping Xiang 1
Daniel Ellard 1
Udi Wieder 1
Qi Zhang 1
Kevin Greenan 1
Medha Bhadkamkar 1
Fernando Farfán 1
Adam Buchsbaum 1
Marshall Mckusick 1
Min Xu 1
Stefan Savage 1
Vesna Pavlović 1
Hyeongseog Kim 1
Robert Haas 1
Kristal Pollack 1
Jehoshua Bruck 1
Feng Zheng 1
Matthew Wachs 1
Karan Sanghi 1
Fernando André 1
Paulo Sousa 1
Jun Yuan 1
Yang Zhan 1
John Esmet 1
Sabrina Vimercati 1

Affiliation Paper Counts
Barcelona Supercomputing Center 1
Massachusetts Institute of Technology 1
University of Southern California, Information Sciences Institute 1, Inc. 1
University of Cyprus 1
Sun Microsystems 1
Yale University 1
Indian Institute of Science 1
Earlham College 1
Rutgers University 1
Temple University 1
University of California, Santa Barbara 1
University of Bergamo 1
Oracle Corporation 1
Complutense University of Madrid 1
Al Baha University 1
Dartmouth College 1
National Taichung Institute of Technology Taiwan 1
The University of North Carolina at Chapel Hill 1
University of California, Berkeley 1
Dickinson College, Pittsburgh 1
Politecnico di Milano 1
New Jersey Institute of Technology 1
University of Denver 1
University of Washington Seattle 1
Los Alamos National Laboratory 1
Dankook University 1
The University of Tennessee System 1
Saint Petersburg State Polytechnical University 1
Universitat Politecnica de Catalunya 1
Cornell University 1
Tamkang University 1
Harvard University 1
The University of British Columbia 1
Santa Clara University 1
University of Durham 1
Symantec Corporation 1
Harvard School of Engineering and Applied Sciences 2
University of Belgrade 2
Pohang University of Science and Technology 2
California Institute of Technology 2
Johannes Gutenberg University Mainz 2
New Mexico Institute of Mining and Technology 2
Ben-Gurion University of the Negev 2
University of Alabama at Birmingham 2
University of Tokyo 2
University of Virginia 2
University of Twente 2
San Diego State University 2
National Tsing Hua University 2
Hongik University 2
The College of William and Mary 2
University of Pittsburgh 2
Sandia National Laboratories 2
Stanford University 2
National Taipei University of Technology 2
Google Inc. 2
Ohio State University 2
Virginia Commonwealth University 2
Harvey Mudd College 2
Ewha Women's University 2
Ajou University 3
University of Texas at San Antonio 3
IBM India Research Laboratory New Delhi 3
Northwestern University 3
Duke University 3
Purdue University 3
National Chiao Tung University Taiwan 3
University of Tennessee, Knoxville 3
National University of Singapore 3
Xiamen University 3
Oak Ridge National Laboratory 3
National University of Defense Technology China 3
University Michigan Ann Arbor 3
University of Milan 3
Korea Advanced Institute of Science & Technology 3
Microsoft Research Cambridge 3
Microsoft Research Asia 3
HP Labs 4
University of Ljubljana 4
University of Massachusetts Amherst 4
University of California, Riverside 4
University of Southern California 4
Seagate Research 4
Samsung Electronics 4
University of Ioannina 4
North Carolina State University 4
New York University 4
Academia Sinica Taiwan 4
Northeastern University 4
IBM Almaden Research Center 5
Florida State University 5
University of Lisbon 5
Pennsylvania State University 5
National Taiwan University of Science and Technology 5
University of California, Los Angeles 5
Foundation for Research and Technology-Hellas 5
NEC Laboratories America, Inc. 5
Microsoft 6
Johns Hopkins University 6
University of California, Irvine 6
University of California, San Diego 6
Intel Corporation 6
Date Storage Institute, A-Star, Singapore 6
University of Science and Technology of China 7
University of Nebraska - Lincoln 7
Argonne National Laboratory 7
EMC Corporation 7
Chinese University of Hong Kong 8
Wayne State University 8
Texas A and M University 8
Princeton University 9
IBM Zurich Research Laboratory 9
IBM Thomas J. Watson Research Center 10
Florida International University 10
University of Illinois at Urbana-Champaign 12
Auburn University 12
Huazhong University of Science and Technology 12
National Taiwan University 13
Carnegie Mellon University 16
Hanyang University 17
Seoul National University 17
University of California, Santa Cruz 19
University of Toronto 19
Tsinghua University 20
Microsoft Research 22
Stony Brook University 35
University of Wisconsin Madison 36

ACM Transactions on Storage (TOS) - Special Issue USENIX FAST 2015

Volume 11 Issue 4, November 2015 Special Issue USENIX FAST 2015
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Volume 10 Issue 4, October 2014 Special Issue on Usenix Fast 2014
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