Conference Information

MSST 2026: International Conference on Massive Storage Systems and Technology

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MSST
Submission Date:
2026-04-14 Extended
Notification Date:
2026-05-01
Conference Date:
2026-06-01
Location:
Santa Clara, California, USA
Years:
CCF: B   Viewed: 61703   Tracked: 66   Attend: 17

Call For Papers

MSST 2026 (International Conference on Massive Storage Systems and Technology) is a CCF B conference held in Santa Clara, California, USA on 2026-06-01. The paper submission deadline is 2026-04-14 (extended). Acceptance notifications are sent on 2026-05-01.

MSST 2026 will be held at Santa Clara University, in the heart of Silicon Valley, and offer a full week dedicated to storage technology through both an industrial and a research track. The MSST research track provides a forum for top-quality original storage research, a place where academic researchers and industry practitioners can share findings and challenges in storage technology. Submissions will be judged on their originality, technical merit, topical relevance, and impact. Topics The Research Program Committee encourages the submission of full and short research papers on the implementation, design, and analysis of file and storage systems. Specific areas of interest include, but are not limited to: Application- and workload-specific storage Archival and backup storage Auditing and provenance Deduplication and compression Caching, tiering, and replication Data protection and recovery Disaggregated and distributed storage Storage on the edge Energy-efficient storage Exascale storage architecture and design Experiences with real-world systems and data storage challenges File systems Flash/SSD Heterogeneous memory/storage systems Memory-centric storage systems New storage hardware, DPUs, persistent memory Next-generation storage (DNA, glass) Performance modeling and prediction for storage Usability and quality of service for storage Security and privacy of storage Storage for emerging applications Storage reliability, erasure coding Storage virtualization Storage systems for ML and applying ML to storage systems
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