Optimizing File Replication over Limited-Bandwidth Networks using Remote Differential Compression
Remote Differential Compression (RDC) protocols can efficiently update files over a limited-bandwidth network when two sites have roughly similar files; no site needs to know the content of another’s files a priori. We present a heuristic approach to identify and transfer the file differences that is based on finding similar files, subdividing the files into chunks, and comparing chunk signatures. Our work significantly improves upon previous protocols such as LBFS and RSYNC in three ways. Firstly, we present a novel algorithm to efficiently find the client files that are the most similar to a given server file. Our algorithm requires 96 bits of meta-data per file, independent of file size, and thus allows us to keep the metadata in memory and eliminate the need for expensive disk seeks. Secondly, we show that RDC can be applied recursively to signatures to reduce the transfer cost for large files. Thirdly, we describe new ways to subdivide files into chunks that identify file differences more accurately. We have implemented our approach in DFSR, a state-based multi-master file replication service shipping as part of Windows Server 2003 R2. Our experimental results show that similarity detection produces results comparable to LBFS while incurring a much smaller overhead for maintaining the metadata. Recursive signature transfer further increases replication efficiency by up to several orders of magnitude.