"Take a byte out of file-system latency"

Shark

A Secure Cooperative File System

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Our Goal

Network file systems offer a powerful, transparent interface for accessing remote data. Unfortunately, in current network file systems like NFS, clients fetch data from a central file server, inherently limiting the system's ability to scale to many clients. While recent distributed (peer-to-peer) systems have managed to eliminate this scalability bottleneck, they are often exceedingly complex and provide non-standard models for administration and accountability. Shark is a novel file system that retains the best of both worlds---the scalability of distributed systems with the simplicity of central servers.

Shark is a distributed file system designed for large-scale, wide-area deployment, while also providing a drop-in replacement for local-area file systems. Shark introduces a novel cooperative-caching mechanism, in which mutually-distrustful clients can exploit each others' file caches to reduce load on an origin file server. Using a distributed index, Shark clients find nearby copies of data, even when files originate from different servers. Performance results show that Shark can greatly reduce server load and improve client latency for read-heavy workloads both in the wide and local areas, while still remaining competitive for single clients in the local area. Thus, Shark enables modestly-provisioned file servers to scale to hundreds of read-mostly clients while retaining traditional usability, consistency, security, and accountability.

What is Shark?

Shark is a network file system specifically designed to support widely distributed applications. Rather than manually replicate program files, users can place a distributed application and its entire run-time environment in an exported file system, and simply execute the program directly from the file system on all nodes.

Of course, the big challenge faced by Shark is scalability. Shark scales to large numbers of clients through a locality-aware cooperative cache. When reading an uncached file, a Shark client avoids transferring the file or even chunks of the file from the server, if the same data can be fetched from another, preferably nearby, client. For world-readable files, clients will even download nearby cached copies of identical files---or even file chunks---originating from different servers.

Shark leverages Coral, a locality-aware, peer-to-peer distributed index, to coordinate client caching. Shark clients form self-organizing clusters of well-connected machines. When multiple clients attempt to read identical data, these clients locate nearby replicas and stripe downloads from each other in parallel. Thus, even modestly-provisioned file servers can scale to hundreds, possibly thousands, of clients making mostly read accesses.

Shark receives funding as part of the IRIS peer-to-peer research and development project, sponsored by NSF.




NYU Secure Computer Systems / Project IRIS   ·   7th Floor · 715 Broadway · New York, NY 10003 · USA