Jeanna Neefe Matthews, Drew Roselli, Adam Costello, Randy Wang, and Thomas Anderson. Improving the Performance of Log-structured File Systems with Adaptive Methods. Proc. Sixteenth ACM Symposium on Operating Systems Principles (SOSP), October 1997, pages 238 - 251.
Abstract:
File system designers today face a dilemma, a
log-structured file system (LFS) can offer superior performance for many common
workloads such as those with frequent small writes, read traffic that is
predominantly absorbed by the cache, and sufficient idle time to clean the log.
However, an LFS has poor performance for other workloads, such as random updates
to a full disk with little idle time to clean. In this paper, we show how
adaptive algorithms can be used to enable LFS to provide high performance across
a wider range of workloads. First, we show how to improve LFS write performance
in three ways: by choosing the segment size to match disk and workload
characteristics, by modifying the LFS cleaning policy to adapt to changes in
disk utilization, and by using cached data to lower cleaning costs. Second, we
show how to improve LFS read performance by reorganizing data to match read
patterns. Using trace-driven simulations on a combination of synthetic and
measured workloads, we demonstrate that these extensions to LFS can
significantly improve its performance.