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William J. Bolosky

Researcher at Microsoft

Publications -  82
Citations -  11139

William J. Bolosky is an academic researcher from Microsoft. The author has contributed to research in topics: File system fragmentation & Versioning file system. The author has an hindex of 46, co-authored 82 publications receiving 10579 citations. Previous affiliations of William J. Bolosky include University of Rochester.

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Journal ArticleDOI

Farsite: federated, available, and reliable storage for an incompletely trusted environment

TL;DR: The design of Farsite is reported on and the lessons learned by implementing much of that design are reported, including how to locally caching file data, lazily propagating file updates, and varying the duration and granularity of content leases.

Mach: A New Kernel Foundation for UNIX Development.

TL;DR: Mach as mentioned in this paper is a multiprocessor operating system kernel and environment under development at Carnegie Mellon University, which provides a new foundation for UNIX development that spans networks of uniprocessors and multi-processors.
Proceedings ArticleDOI

Reclaiming space from duplicate files in a serverless distributed file system

TL;DR: This work presents a mechanism to reclaim space from this incidental duplication to make it available for controlled file replication, and includes convergent encryption, which enables duplicate files to be coalesced into the space of a single file, even if the files are encrypted with different users' keys.
Proceedings ArticleDOI

Feasibility of a serverless distributed file system deployed on an existing set of desktop PCs

TL;DR: It is concluded that the measured desktop infrastructure would passably support the proposed serverless distributed file system, providing availability on the order of one unfilled file request per user per thousand days.
Journal ArticleDOI

A study of practical deduplication

TL;DR: In this paper, the authors collected file system content data from 857 desktop computers at Microsoft over a span of four weeks and analyzed the data to determine the relative efficacy of data deduplication, particularly considering whole file versus block-level elimination of redundancy.