We conduct a comprehensive study of file-system code evolution. By analyzing eight years of Linux file-system changes across 5079 patches, we derive numerous new (and sometimes surprising) insights into the file-system development process; our results should be useful for both the development of file systems themselves as well as the improvement of bug-finding tools.

Recent research has shown that applications often incorrectly implement crash consistency. We present the Crash-Consistent File System (ccfs), a file system that improves the correctness of application-level crash consistency protocols while maintaining high performance. A key idea in ccfs is the abstraction of a stream. Within a stream, updates are committed in program order, improving correctness; across streams, there are no ordering restrictions, enabling scheduling flexibility and high performance. We empirically demonstrate that applications running atop ccfs achieve high levels of crash consistency. Further, we show that ccfs performance under standard file-system benchmarks is excellent, in the worst case on par with the highest performing modes of Linux ext4, and in some cases notably better. Overall, we demonstrate that both application correctness and high performance can be realized in a modern file system.

We present WiscKey, a persistent LSM-tree-based key-value store with a performance-oriented data layout that separates keys from values to minimize I/O amplification. The design of WiscKey is highly SSD optimized, leveraging both the sequential and random performance characteristics of the device. We demonstrate the advantages of WiscKey with both microbenchmarks and YCSB workloads. Microbenchmark results show that WiscKey is 2.5× to 111× faster than LevelDB for loading a database (with significantly better tail latencies) and 1.6× to 14× faster for random lookups. WiscKey is faster than both LevelDB and RocksDB in all six YCSB workloads.

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Energy consumption is becoming an increasingly important issue in storage systems, especially for high performance data centers and network servers. In this paper, we introduce a family of energy-efficient disk layouts that generalize the data mirroring of a conventional RAID1 system. The scheme called DiskGroup distributes the workload between the primary disks and secondary disks based on the characteristics of the workload. We develop an analytic model to explore the design space and compute the estimated energy savings and performance as a function of workload characteristics. The analysis shows the potential for significant energy savings over simple RAID1 data mirroring.