Kaiwei Tu, University of Wisconsin–Madison; Kan Wu, Google; Andrea C. Arpaci-Dusseau and Remzi H. Arpaci-Dusseau, University of Wisconsin–Madison
We present Mirror-Optimized Storage Tiering (MOST), a novel tiering-based approach optimized for modern storage hierarchies. The key idea of MOST is to combine the load-balancing advantages of mirroring with the space-efficiency advantages of tiering. Specifically, MOST dynamically mirrors a small amount of hot data across storage tiers to efficiently balance load, avoiding costly migrations. As a result, MOST is as space-efficient as classic tiering while achieving better bandwidth utilization under I/O-intensive workloads. We implement MOST in Cerberus, a user-level storage management layer based on CacheLib. We show the efficacy of Cerberus through a comprehensive empirical study: across a range of static and dynamic workloads, Cerberus achieves better throughput than competing approaches on modern storage hierarchies especially under I/O-intensive and dynamic workloads.
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author = {Kaiwei Tu and Kan Wu and Andrea C. Arpaci-Dusseau and Remzi H. Arpaci-Dusseau},
title = {Getting the {MOST} out of your Storage Hierarchy with {Mirror-Optimized} Storage Tiering},
booktitle = {24th USENIX Conference on File and Storage Technologies (FAST 26)},
year = {2026},
isbn = {978-1-939133-53-3},
address = {Santa Clara, CA},
pages = {561--578},
url = {https://www.usenix.org/conference/fast26/presentation/tu},
publisher = {USENIX Association},
month = feb
}
