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This thesis considers two related issues: the impact of disk layout on file system throughput and the integration of transaction support file systems. Historic file system designs have optimized for reading, as read throughput was the I/O performance bottleneck. Since increasing main-memory cache sizes effectively reduce disk read traffic [BAKER91], disk write performance has become the I/O performance bottleneck [OUST89]. This thesis presents both simulation and implementation analysis of the performance of read-optimized and write-optimized file systems. An example of a file system with a disk layout optimized for writing is a log-structured file system, where writes are bundled and written sequentially. Empirical evidence in [ROSE90], [ROSE91], and [ROSE92] indicates that a log-structured file system provides superior write performance and equivalent read performance to traditional file systems. This thesis analyzes and evaluates the log-structured file system presented in [ROSE91], isolating some of the critical issues in its design. Additionally, a modified design addressing these issues is presented and evaluated. Log-structured file systems also offer the potential for superior integration of transaction processing into the system. Because log-structured file systems use logging techniques to store files, incorporating transaction mechanisms into the file system is a natural extension. This thesis presents the design, implementation, and analysis of both user-level transaction management on read and write-optimized file systems and embedded transaction management in a write optimized file system. This thesis shows that both log-structured file systems and simple read-optimized file systems can attain nearly 100% of the disk bandwidth when I/Os are large or sequential. The improved write performance of LFS discussed in [ROSE92] is only attainable when garbage collection overhead is small, and in nearly all of the workloads examined, performance of LFS is comparable to that of read-optimized file system. On transaction processing workloads where a steady stream of small, random I/Os are issued, garbage collection reduces LFS throughput by 35% ot 40%.