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MSST 2017 : 33nd International Conference on Massive Storage Systems and Technologies 2017


Conference Series : IEEE Conference on Mass Storage Systems and Technologies
When May 15, 2017 - May 12, 2017
Where Santa Clara, California (SCU)
Abstract Registration Due Feb 10, 2017
Submission Deadline Feb 17, 2017
Notification Due Mar 31, 2017
Final Version Due Apr 28, 2017
Categories    storage systems

Call For Papers

The 33rd International Conference on Massive Storage Systems and Technologies (MSST 2017) will be held, once again, on the beautiful campus of Santa Clara University, in the heart of Silicon Valley, May 15 – May 19,2017, offering five days dedicated to storage technology. As on previous occasions, the conference will include two days of peer-reviewed research papers and a Vendor Exhibition, along with many other events.


- Presentations (May 16 - 17, 2017)

The Program Committee requests presentation proposals on issues in designing, building, maintaining, and migrating large-scale systems that implement databases and other kinds of large, typically persistent, web-scale stores (HSM, NoSQL, key-value stores, etc.), and archives at scales of tens of petabytes to exabytes and beyond. Potential presentation topics include but are not limited to:

- Web-scale, corporate, and exa-scale HPC storage systems in the 10+ Petabyte to Exabyte and beyond size, which may require high-bandwidth or transactional access, and which may require rapid growth and occasional wholesale data migration;

- Archive design and implementation for large and/or long-lived stores;

- Issues around hardware or software components (e.g., media such as disk, tape, or flash: NoSQL databases; open source clustering tools, etc.) that relate to designing very large scale storage systems.

During the 2016 MSST presentation track, sessions included the following:

 Application- and Workload-Specific Workflows;
 Leveraging Disk for Large-Scale, Long-Term Storage Applications;
 Trends in FLASH Technology Relevant to Large-Scale Systems;
Evolving Semantics for Object Storage;

Submit presentation proposals through our contact page at:


- Research Papers (May 18 - 19, 2017)

The Research Program Committee requests the submission of research papers on the implementation, design, and analysis of file and storage systems. Specific areas of interest include, but are not limited to:

- Exascale storage architecture and design
- Parallel and distributed file systems
- Designs of integrating parallel programming and distributed storage systems
- Storage security and privacy
- Storage provenance
- Scalable metadata management
- Techniques for building extremely scalable and distributed storage systems
- Cloud storage systems and global-scale storage
- Performance modeling and analysis of storage systems
- Experiences with real-world systems and data storage challenges
- Data protection and recovery
- Data archiving
- Data compression and deduplication
- Long-term data preservation and management
- Storage for virtualized environments
- Disk and flash based primary and cold storage systems
- File systems for shingled magnetic recording hard disk drives
- File systems for solid state disk drives
- Tiered storage
- Storage virtualization
- Networked storage architectures
- New storage APIs: object storage, key-value stores, and others
- I/O stacks for low-latency storage devices
- Storage class memory devices and systems, such as phase change memory
- Storage solutions usability and consumability

As is traditional, MSST will solicit short (4-6 pages) and full (8-14 pages) papers. References are not included in page
counts. Paper formats should adhere to the IEEE conference templates available at"
Submission procedures will be established soon.

Research Track Abstract Deadline: Fri, February 10, 2017
Research Track Submission Deadline: Fri, February 17, 2017
Research Track Notification Due: Fri, March 31, 2017
Research Track Final Version Due: Fri, April 28, 2017
Conference: May 15th - May 19th, 2017
Research Track: May 18th - May 19th, 2017

Program Co-chairs
● Thomas Schwarz, Marquette University
● Aleatha Parker-Wood, Center for Advanced Machine Learning at Symantec

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