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Duplication of data in storage systems is becoming increasingly common. We introduce I/O Deduplication, a storage optimization that utilizes content similarity for improving I/O performance by eliminating I/O operations and reducing the mechanical delays during I/O operations. I/O Deduplication consists of three main techniques: content-based caching, dynamic replica retrieval, and selective duplication. Each of these techniques is motivated by our observations with I/O workload traces obtained from actively-used production storage systems, all of which revealed surprisingly high levels of content similarity for both stored and accessed data. Evaluation of a prototype implementation using these workloads revealed an overall improvement in disk I/O performance of 28-47% across these workloads. Further breakdown also showed that each of the three techniques contributed significantly to the overall performance improvement.
3 weeks of traces for the following workloads:
|http://doomsday.cs.fiu.edu/iodedup/mail.tar.gz||CS department's mail server traces. It includes all the inboxes of mails in the CS department.|
|http://doomsday.cs.fiu.edu/iodedup/homes.tar.gz||Research group activities: developing, testing, experiments, technical writing, plotting.|
|http://doomsday.cs.fiu.edu/iodedup/web-vm.tar.gz||CS department webmail proxy and online course management.|
The traces files are in ASCII and each record is as follows:
[ts] [pid] [process] [lba] [size in 512 Bytes blocks] [Write or Read] [major device number] [minor device number] [MD5 per 4096 Bytes]
In the case of the home traces, the format is different for the digests:
[ts] [pid] [process] [lba] [size in 512 Bytes blocks] [Write or Read] [major device number] [minor device number] [MD5 per 512 Bytes]