USENIX 2019

USENIX 2019
2019 USENIX Annual Technical Conference
Event in series	USENIX
Dates	2019/07/10 (iCal) - 2019/07/12
Homepage:	https://www.usenix.org/conference/atc19
Location
Location:	Renton, WA, USA
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Important dates
Papers:	2019/03/28
Submissions:	2019/01/10
Notification:	2019/04/16
Camera ready due:	2019/05/30
Papers:	Submitted 356 / Accepted 71 (19.9 %)
Committees
PC chairs:	Dahlia Malkhi, Dan Tsafrir
Table of Contents

USENIX ATC´19

2019 USENIX Annual Technical Conference. USENIX ATC brings together leading systems researchers for the presentation of cutting-edge systems research and the opportunity to gain insight into a wealth of must-know topics, including virtualization, system and network management and troubleshooting, cloud and edge computing, security, privacy, and trust, mobile and wireless, and more.

As part of our commitment to open access to research, the full Proceedings are free and open to the public on the technical sessions page. Presentation slides are posted as we receive them, and video recordings are posted within a few weeks of the end of the event.

The 2019 USENIX Annual Technical Conference will take place on July 10–12, 2019, at the Hyatt Regency Lake Washington in Renton, WA, USA. Sponsored by USENIX, the Advanced Computing Systems Association

Important Dates

USENIX ATC '19 Call for Papers

• Submission deadline: Thursday, January 10, 2019, 3:00 pm PST (note: no abstract registration)
• Beginning of authors' response period: Tuesday, March 26, 2019
• Authors' response due: Thursday, March 28, 2019, 11:59 pm PDT
• Notification to authors: Tuesday, April 16, 2019, 11:59 pm PDT
• Camera-ready papers due: Thursday, May 30, 2019

Conference Organizers

Program Co-Chairs

• Dahlia Malkhi, VMware Research and Calibra
• Dan Tsafrir, Technion—Israel Institute of Technology & VMware Research

Program Committee

• Nitin Agrawal, ThoughtSpot
• Irfan Ahmad, Magnition
• Deniz Altinbuken, Google
• Nadav Amit, VMware Research Group
• Saurabh Bagchi, Purdue University
• Mahesh Balakrishnan, Yale University and Facebook
• Antonio Barbalace, Stevens Institute of Technology
• Andrew Baumann, Microsoft Research Redmond
• Adam Belay, Massachusetts Institute of Technology
• Ken Birman, Cornell University
• Edward Bortnikov, Yahoo
• Herbert Bos, Vrije Universiteit Amsterdam
• Andre Brinkmann, Johannes Gutenberg-University Mainz
• Edouard Bugnion, École Polytechnique Fédérale de Lausanne (EPFL)
• Randal Burns, Johns Hopkins University
• Anton Burtsev, University of California, Irvine
• Haibo Chen, Shanghai Jiao Tong University
• Vijay Chidambaram, The University of Texas at Austin and VMware Research
• Asaf Cidon, Barracuda Networks
• Austin Clements, Google
• David Cock, ETH Zurich
• Paolo Costa, Microsoft Research
• John Criswell, University of Rochester
• Charlie Curtsinger, Grinnell College
• Dilma Da Silva, Texas A&M University
• Nathan Dautenhahn, Rice University
• Eyal de Lara, University of Toronto
• Christina Delimitrou, Cornell University
• Angela Demke Brown, University of Toronto
• Fred Douglis, Perspecta Labs
• Eric Eide, University of Utah
• Michael Factor, IBM Research—Haifa
• Pascal Felber, University of Neuchâtel
• Christof Fetzer, TU Dresden
• Moshe Gabel, University of Toronto
• Ada Gavrilovska, Georgia Institute of Technology
• Phillip Gibbons, Carnegie Mellon University
• Cristiano Giuffrida, Vrije Universiteit Amsterdam
• Ashvin Goel, University of Toronto
• Boris Grot, University of Edinburgh
• Steven Hand, Google
• Liting Hu, Florida International University
• Yu Hua, Huazhong University of Science and Technology
• Jian Huang, University of Illinois at Urbana-Champaign
• Bill Jannen, Williams College
• Sudarsun Kannan, Rutgers University
• Manos Kapritsos, University of Michigan
• Kimberly Keeton, Hewlett Packard Labs
• Samira Khan, University of Virginia
• Taesoo Kim, Georgia Institute of Technology
• Sam King, University of California, Davis
• Aasheesh Kolli, The Pennsylvania State University
• Dejan Kostic, KTH Royal Institute of Technology
• Geoff Kuenning, Harvey Mudd College
• Patrick P.C. Lee, The Chinese University of Hong Kong
• Xing Lin, NetApp
• Ethan Miller, University of California, Santa Cruz, and Pure Storage
• Changwoo Min, Virginia Polytechnic Institute and State University
• Adam Morrison, Tel Aviv University
• Gilles Muller, Inria
• Dushyanth Narayanan, Microsoft Research
• David Nellans, NVIDIA
• Ed Nightingale, Microsoft Research
• Sam H. Noh, UNIST (Ulsan National Institute of Science and Technology)
• Aurojit Panda, New York University
• Peter Pietzuch, Imperial College London
• Don Porter, The University of North Carolina at Chapel Hill
• Michael Reiter, The University of North Carolina at Chapel Hill
• Scott Rixner, Rice University
• Timothy Roscoe, ETH Zurich
• Chris Rossbach, The University of Texas at Austin and VMware Research
• Leonid Ryzhyk, VMware Research
• Bianca Schroeder, University of Toronto
• Liuba Shrira, Brandeis University
• Keith A. Smith, NetApp
• Patrick Stuedi, IBM Research
• Michael Stumm, University of Toronto
• Ryan Stutsman, University of Utah
• Steve Swanson, University of California, San Diego
• Michael Swift, University of Wisconsin−Madison
• Nisha Talagala, Pyxeda AI
• Theodore Ts'o, Google
• Chia-Che Tsai, Texas A&M University
• Joseph Tucek, Amazon
• Haris Volos, Google
• Marko Vukolic, IBM Research Zurich
• Carl Waldspurger, Carl Waldspurger Consulting
• Ric Wheeler, Facebook
• Dan Williams, IBM T.J. Watson Research Center
• Youjip Won, Korea Advance Institute of Science and Technology (KAIST)
• Gala Yadgar, Technion—Israel Institute of Technology
• Yuval Yarom, University of Adelaide and Data61
• Erez Zadok, Stony Brook University
• Zheng Zhang, Rutgers University
• Extended Review Committee
• Irina Calciu, VMWare Research Group
• Orr Dunkelman, University of Haifa
• Ittay Eyal, Technion—Israel Institute of Technology
• David Grove, IBM Research
• Ajay Gulati, ZeroStack
• Tim Harris, Amazon UK
• Gernot Heiser, University of New South Wales
• Asim Kadav, NEC Labs
• Julia Lawall, Inria/LIP6
• Kfir Lev-Ari, Apple
• Carlos Maltzahn, University of California, Santa Cruz
• Jason Nieh, Columbia University
• Erik Riedel, EMC
• Mark Silberstein, Technion—Israel Institute of Technology
• Animesh Trivedi, Vrije Universiteit Amsterdam
• Ymir Vigfusson, Emerson University
• Lluis Vilanova, Technion—Israel Institute of Technology
• Yang Wang, Ohio State University
• Michael Wei, VMWare Research Group
• Keith Winstein, Stanford University
• Guoqing (Harry) Xu, University of California, Los Angeles
• Noa Zilberman, University of Cambridge
• Best of the Rest Session Co-Chairs
• Amy Tai, VMware Research
• Chia-Che Tsai, Texas A&M University
• Lightning Talks Co-Chairs
• Deniz Altinbuken, Google
• Aasheesh Kolli, The Pennsylvania State University and VMware Research
• Submissions Co-Chairs
• Lalith Suresh, VMware Research
• Gerd Zellweger, VMware Research

The 2019 USENIX Annual Technical Conference (USENIX ATC '19) seeks original, high-quality submissions that improve and further the knowledge of computing systems, with an emphasis on implementations and experimental results. We are interested in systems of all scales, from small embedded mobile devices to data centers and clouds. The scope of USENIX ATC covers all practical aspects related to systems software, including: operating systems; runtime systems; parallel and distributed systems; storage; networking; security and privacy; virtualization; software-hardware interactions; performance evaluation and workload characterization; reliability, availability, and scalability; energy/power management; bug-finding, tracing, analyzing, and troubleshooting.

We welcome experience submissions that clearly articulate lessons learned, as well as submissions that refute prior published results. We value submissions more highly if they are accompanied by clearly defined artifacts not previously available, including traces, original data, source code, or tools developed as part of the submitted work. We particularly encourage new ideas and approaches.

Briefly, we received 356 submissions and accepted 71 (19.9% acceptance rate) through a double-blind, two-rounds review process.