Summary: 1
Abstract
File system designers today face a dilemma. A log­struc­
tured 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 ran­
dom updates to a full disk with little idle time to clean. In this
paper, we show how adaptive algorithms can be used to en­
able LFS to provide high performance across a wider range
of workloads. First, we show how to improve LFS write per­
formance 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 reorga­
nizing data to match read patterns. Using trace­driven simu­
lations on a combination of synthetic and measured
workloads, we demonstrate that these extensions to LFS can

Source: Anderson, Tom - Department of Computer Science and Engineering, University of Washington at Seattle

Collections: Computer Technologies and Information Sciences