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Abstract: With a vast number of resources being committed to reformatting into digital form, we need to consider how we can ensure that digital information will continue to be accessible over a prolonged period of time. This chapter first outlines the general problem of information in digital form disappearing. It then looks closely at five key factors that pose problems for digital longevity. Finally, we turn our attention to a series of suggestions that are likely to improve the longevity of digital information, focusing primarily on metadata. This chapter was written for the library, museum, and archives communities. However, the observations will be useful for all communities wishing to ensure the longevity of any type of digital information.

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Abstract: The promise has been made: ``Digital information is forever. It doesn't deteriorate and requires little in the way of material media.'' So said one of the chieftains of the emerging digital age, computer-chip maker Andy Grove, the head of the Intel Corporation. Another chieftain, Librarian of Congress James H. Billington, has set about digitizing the world?s largest library so that its contents can become accessible by anyone, from anywhere, forever. But a shadow has fallen. ``It is only slightly facetious,'' wrote RAND researcher Jeff Rothenberg in Scientific American, ``to say that digital information lasts forever—or five years, whichever comes first.''

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Randal Burns, Robert Rees, and Darrell D. E. Long. Efficient data distribution in a web server farm. Internet Computing, pages 56–65, 2001.
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Randal Burns, Robert Rees, and Darrell D. E. Long. Safe caching in a distributed file system for network attached storage. In Proceedings of the 14th International Parallel & Distributed Processing Symposium (IPDPS 2000). IEEE, May 2000.
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Randal Burns, Robert Rees, and Darrell D. E. Long. Consistency and locking for distributing updates to web servers using a file system. In Workshop on Performance and Architecture of Web Servers. ACM, June 2000.
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Randal Burns. Data Management in a Distributed File System for Storage Area Networks. Ph.d. dissertation, Department of Computer Science, University of California, Santa Cruz, March 2000.
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Xin Li, Michael C. Huang, Kai Shen, and Lingkun Chu. An empirical study of memory hardware errors in a server farm. In Proceedings of the Third Workshop on Hot Topics in System Dependability (HotDep '07), June 2007.
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Han Li and Qian Huan-yan. Parallelized network coding with SIMD instruction sets. In Proceedings of the 2008 International Symposium on Computer Science and Computational Technology, pages 364–369, 2008.
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Jinyuan Li, Maxwell Krohn, David Mazières, and Dennis Shasha. Secure untrusted data repository (SUNDR). In Proceedings of the 6th Symposium on Operating Systems Design and Implementation (OSDI), December 2004.
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Yan Li, Darrell D. E. Long, and Ethan L. Miller. Understanding data survivability in archival storage systems. In Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR 2012), June 2012.
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Xin Li, Kai Shen, Michael C. Huang, and Lingkun Chu. A memory soft error measurement on production systems. In Proceedings of the 2007 USENIX Annual Technical Conference, pages 275–280, June 2007.
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Kester Li, Roger Kumpf, Paul Horton, and Thomas Anderson. A quantitative analysis of disk drive power management in portable computers. In Proceedings of the Winter 1994 USENIX Technical Conference, pages 279–291, San Francisco, CA, January 1994.
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Mark Lillibridge, Sameh Elnikety, Andrew Birrell, Mike Burrows, and Michael Isard. A cooperative Internet backup scheme. In Proceedings of the 2003 USENIX Annual Technical Conference, pages 29–42, San Antonio, TX, 2003.
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Witold Litwin, Rim Moussa, and Thomas Schwarz. LH*RS – a highly-available scalable distributed data structure. ACM Transactions on Database Systems, 30(3):769–811, 2005.
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Witold Litwin, Marie-Anna Neimat, and Donovan A. Schneider. LH*—a scalable, distributed data structure. ACM Transactions on Database Systems, 21(4):480–525, 1996.
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Chuanyi Liu1, Yu Gu, Linchun Sun, Bin Yan, and Dongsheng Wang. R-ADMAD: High reliability provision for large-scale de-duplication archival storage systems. In Proceedings of the 23rd International Conference on Supercomputing (ICS '09), pages 370–379, June 2009.
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Zhong Liu, Nong Xiao, and Xing-Ming Zhou. RDIM: Rdim: A self-adaptive and balanced distribution for replicated data in scalable storage clusters. Lecture Notes in Computer Science, 3758:21–32, 2005.
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Ning Liu, Jason Cope, Philip H. Carns, Christopher D. Carothers, Robert B. Ross, Gary Grider, Adam Crume, and Carlos Maltzahn. On the role of burst buffers in leadership-class storage systems. In Proceedings of the 28th IEEE Conference on Mass Storage Systems and Technologies, pages 1–11, 2012.
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Jed Liu, Michael D. George, K. Vikram, Xin Qi, Lucas Waye, and Andrew C. Myers. Fabric: A platform for secure distributed computation and storage. In Proceedings of the 22nd ACM Symposium on Operating Systems Principles (SOSP '09), pages 321–334, Big Sky, MT, October 2009.
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llnl:alc:
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long:compcon95:
Darrell D. E. Long, Patrick E. Mantey, Craig M. Wittenbrink, Theodore R. Haining, and Bruce R. Montague. REINAS: the real-time environmental information network and analysis system. In Proceedings of the IEEE Computer Society Compcon '95, pages 482–487, San Francisco, March 1995. IEEE.
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Darrell D. E. Long, Bruce R. Montague, and Luis-Felipe Cabrera. Swift/RAID: A distributed RAID system. Computing Systems, 7(3):333–359, 1994.
long:icdcs89:
Darrell D. E. Long, John L. Carroll, and Kris Stewart. The reliability of regeneration-based replica control protocols. In Proceedings of the 9th International Conference on Distributed Computing Systems (ICDCS '89), pages 465–473, Newport Beach, June 1989. IEEE.
long:icdcs93:
Darrell D. E. Long, Carol Osterbrock, and Luis-Felipe Cabrera. Providing performance guarantees in an fddi network. In Proceedings of the 13th International Conference on Distributed Computing Systems (ICDCS '93), pages 328–336, Pittsburgh, May 1993. IEEE.
long:icde89:
Darrell D. E. Long and Jehan-François Pâris. Regeneration protocols for replicated objects. In Proceedings of the 5th International Conference on Data Engineering (ICDE '89), pages 538–545, Los Angeles, February 1989. IEEE.
long:icde91:
Darrell D. E. Long and Jehan-François Pâris. Voting with regenerable volatile witnesses. In Proceedings of the 7th International Conference on Data Engineering (ICDE '91), pages 112–119, Kobe, Japan, April 1991. IEEE.
long:ipccc01:
Darrell D. E. Long. A technique for managing mirrored disks. In Proceedings of the 20th IEEE International Performance, Computing and Communications Conference (IPCCC '01), pages 272–277, Phoenix, April 2001. IEEE.
long:ipccc89:
Darrell D. E. Long, Jehan-François Pâris, and John L. Carroll. Reliability of replicated data objects. In Proceedings of the 8th IEEE International Performance, Computing and Communications Conference (IPCCC '89), pages 402–406, Phoenix, March 1989. IEEE.
long:ipccc97:
Darrell D. E. Long and Jehan-François Pâris. Voting without version numbers. In Proceedings of the 16th IEEE International Performance, Computing and Communications Conference (IPCCC '97), pages 139–145, Phoenix, February 1997. IEEE.
long:lgp87:
Darrell D. E. Long. Optimistic algorithms for replicated data management. In Proceedings of the 2nd Workshop on Large-Grained Parallelism, pages 58–59, Carnegie-Mellon University, November 1987.
long:mss93:
Darrell D. E. Long and Madhukar N. Thakur. Scheduling real-time disk transfers for continuous media applications. In Proceedings of the 12th IEEE Symposium on Mass Storage Systems, pages 227–232, Monterey, April 1993. IEEE.
long:osr:
Darrell D. E. Long. A note on bit-mapped free sector management. Operating Systems Review, 27(2):7–9, April 1993.
long:pdp96:
Darrell D. E. Long and Jehan-François Pâris. A leaner, more efficient, available copy protocol. In Proceedings of the Syposium on Parallel and Distributed Processing (PDP '96), pages 400–407, New Orleans, October 1996. IEEE.
long:ps95:
Darrell D. E. Long and John L. Carroll. Progress in Simulation II, chapter Using Simulation to Evaluate Consistency Protocols for Replicated Data. G. W. Zorbrist and J. V. Leonard, Eds. Ablex Publishing, 1995.
long:seke96:
Darrell D. E. Long, Patrick E. Mantey, Eric C. Rosen, Craig M. Wittenbrink, and Bruce Gritton. REINAS: A real-time system for managing environmental data. In Proceedings of the 8th Software Engineering and Knowledge Engineering Conference (SEKE 1996), pages 293–300, Lake Tohoe, June 1996. SEKE.
long:srds87:
Darrell D. E. Long and Jehan-François Pâris. On improving the availability of replicated files. In Proceedings of the 6th Symposium on Reliable Distributed Systems (SRDS '87), pages 77–83, Williamsburg, March 1987. IEEE.
long:srds88:
Darrell D. E. Long and Jehan-François Pâris. A realistic evaluation of optimistic dynamic voting. In Proceedings of the 7th Symposium on Reliable Distributed Systems (SRDS '88), pages 129–137, Columbus, October 1988. IEEE.
long:srds91:
Darrell D. E. Long, John L. Carroll, and C. J. Park. A study of the reliability of Internet sites. In Proceedings of the 10th Symposium on Reliable Distributed Systems (SRDS '91), pages 177–186, Pisa, September 1991. IEEE.
long:srds95:
Darrell D. E. Long, Andrew Muir, and Richard Golding. A longitudinal study of internet host reliability. In Proceedings of the 14th Symposium on Reliable Distributed Systems (SRDS '95), pages 2–9, Bad Neuenahr, Germany, September 1995. IEEE.

Abstract: An accurate estimate of host reliability is important for correct analysis of many fault-tolerance and replication mechanisms. In a previous study, we estimated host system reliability by querying a large number of hosts to find how long they had been functioning, estimating the mean time-to-failure (MTTF) and availability from those measures, and in turn deriving an estimate of the mean time-to-repair (MTTR). However, this approach had a bias towards more reliable hosts that could result in overestimating MTTR and underestimating availability. To address this bias we have conducted a second experiment, using a fault-tolerant replicated monitoring tool. This tool directly measures TTF, TTR, and availability by polling many sites frequently from several locations. We find that these more accurate results generally confirm and improve our earlier estimates. We also find that failure and repair are unlikely to follow Poisson processes.

long:toc89:
Darrell D. E. Long, John L. Carroll, and Kris Stewart. Estimating the reliability of regeneration-based replica control protocols. IEEE Transactions on Computers, 38(12):1691–1702, 1989.
long:ucsc-crl-02-35:
Darrell Long, Scott Brandt, Ethan Miller, Feng Wang, Ying Lin, Lan Xue, and Qin Xin. Design and implementation of large scale object-based storage system. Technical Report ucsc-crl-02-35, University of California, Santa Cruz, November 2002.
long:usenix91s:
Darrell D. E. Long and Luis-Felipe Cabrera. Exploiting multiple i/o streams to provide high data-rates. In Proceedings of the Summer 1991 USENIX Technical Conference, pages 31–48, Nashville, June 1991. USENIX.

Abstract: We present an I/O architecture, called Swift, that addresses the problem of data-rate mismatches between the requirements of an application, the maximum data-rate of the storage devices, and the data-rate of the interconnection medium. The goal of Swift is to support integrated continuous multimedia in general purpose distributed systems. In installations with a high-speed interconnection medium, Swift will provide high data-rate transfers by using multiple slower storage devices in parallel. The data-rates obtained with this approach scale well when using multiple storage devices and multiple interconnections. Swift has the flexibility to use any appropriate storage technology, including disk arrays. The ability to adapt to technological advances will allow Swift to provide for ever increasing I/O demands. To address the problem of partial failures, Swift stores data redundantly. Using the UNIX operating system, we have constructed a simplified prototype of the Swift architecture. Using a single Ethernet-based local-area network and three servers, the prototype provides data-rates that are almost three times as fast as access to the local SCSI disk in the case of writes. When compared with NFS, the Swift prototype provides double the data-rate for reads and eight times the data-rate for writes. The data-rate of our prototype scales almost linearly in the number of servers and the number of network segments. Its performance is shown to be limited by the speed of the Ethernet-based local-area network. We also constructed a simulation model to show how the Swift architecture can exploit storage, communication, and processor advances, and to locate the components that will limit I/O performance. In a simulated gigabit/second token ring local-area network the data-rates are seen to scale proportionally to the size of the transfer unit and to the number of storage agents.

long:wmrd90:
Darrell D. E. Long. Analysis of replication control protocols. In Proceedings of the 1st Workshop on the Management of Replicated Data (WMRD '90), pages 117–122, Houston, November 1992. IEEE.
long:wmrd92:
Darrell D. E. Long. A replicated monitoring tool. In Proceedings of the 2nd Workshop on the Management of Replicated Data (WMRD '92), pages 96–99, Montery, November 1992. IEEE.
lorch:fast13:
Jacob R. Lorch, Bryan Parno, James Mickens, Mariana Raykova, and Joshua Schiffman. Shroud: Ensuring private access to large-scale data in the data center. In Proceedings of the 11th USENIX Conference on File and Storage Technologies (FAST), pages 199–213, February 2013.
lorie:jcdl01:
Raymond. A. Lorie. Ensuring the longevity of digital information. In Proceedings of the First ACM/IEEE-CS Joint Conference on Digital Libraries, 2001.
lotspiech:computer02:
Jeffrey Lotspiech, Stefan Nusser, and Florian Pestoni. Broadcast encryption's bright future. IEEE Computer, 35(8):57–63, August 2002.
loui:computer08:
Ronald P. Loui. In praise of scripting: Real programming pragmatism. IEEE Computer, pages 22–26, July 2008.
loverso:usenix93:
Susan J. LoVerso, Marshall Isman, Andy Nanopoulos, William Nesheim, Ewan D. Milne, and Richard Wheeler. \em sfs: A parallel file system for the CM-5. In Proceedings of the Summer 1993 USENIX Technical Conference, pages 291–305, 1993.

Keyword: parallel I/O, multiprocessor file system, pario bib

Comment: They took the Unix file system from SunOS and extended it to run on the CM-5. This involved handling non-power-of-two block sizes, parallel I/O calls, large file sizes, and more encouragement for extents to be allocated. The hardware is particularly suited to RAID 3 with a 16 byte striping unit, although in theory the software could do anything it wants. Geared to data-parallel model. Proc nodes (PNs) contact the timesharing daemon (TD) on the control processor (CP), who gets block lists from the file system, which runs on one of the CPs. The TD then arranges with the disk storage nodes (DSNs) to do the transfer directly with the PNs. Each DSN has 8 MB of buffer space, 8 disk drives, 4 SCSI busses, and a SPARC as controller. Partition managers mount non-local sfs via NFS. Performance results good. Up to 185 MB/s on 118 (2 MB/s) disks.

lowell:sosp97:
David E. Lowell and Peter M. Chen. Free transactions with Rio Vista. In Proceedings of the 16th ACM Symposium on Operating Systems Principles (SOSP '97), pages 92–101, December 1997.
lu:date00:
Yung-Hsiang Lu, Eui-Young Chung, Tajana Simunic, Luca Benini, and Giovanni De Micheli. Quantitative comparison of power management algorithms. In Design Automation and Test in Europe, pages 20–26, March 2000.
lu:ecsl-tr205:
Maohua Lu and Tzi cker Chiueh. Challenges of long-term digital archiving: A survey. Technical Report ECSL-TR-205, Experimental Computer Systems Lab, Stony Brook University, October 2006.
lu:fast02:
Chenyang Lu, Guillermo A. Alvarez, and John Wilkes. Aqueduct: Online data migration with performance guarantees. In Proceedings of the Conference on File and Storage Technologies (FAST), Monterey, CA, January 2002.
lu:glvlsi99:
Yung-Hsiang Lu and Giovanni De Micheli. Adaptive hard disk power management on personal computers. In Proceedings of the Ninth Great Lakes Symposium on VLSI, pages 50–53, 1999.
luby:ieeetit01:
Michael G. Luby, Michael Mitzenmacher, M. Amin Shokrollahi, and Daniel A. Spielman. Efficient erasure correcting codes. IEEE Transactions on Information Theory, 47(2):569–584, February 2001.
lumb:asplos04:
Christopher R. Lumb, Gregory R. Ganger, and Richard Golding. D-SPTF: Decentralized request distribution in brick-based storage systems. In Proceedings of the 11th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), pages 37–47, Boston, MA, 2004.
lumb:fast02:
Christopher R. Lumb, Jiri Schindler, and Gregory R. Ganger. Freeblock scheduling outside of disk firmware. In Proceedings of the Conference on File and Storage Technologies (FAST), Monterey, CA, January 2002.
lumb:fast03:
Christopher R. Lumb, Arif Merchant, and Guillermo A. Alvarez. Façade: Virtual storage devices with performance guarantees. In Proceedings of the 2nd USENIX Conference on File and Storage Technologies (FAST '03), San Francisco, CA, April 2003.
lumb:osdi00:
Christopher R. Lumb, Jiri Schindler, Gregory R. Ganger, David F. Nagle, and Erik Riedel. Towards higher disk head utilization: extracting free bandwidth from busy disk drives. In OSDI'00: Proceedings of the 4th conference on Symposium on Operating System Design & Implementation, pages 7–7, Berkeley, CA, USA, 2000. USENIX Association.
luo:3dpvt2002:
Alison Luo, Ahmed Amer, Scott Speidel, Darrell D. E. Long, and Alex Pang. Visualizing I/O predictability. In Proceedings of the First Symposium on 3D Data Processing Visualization Transmission, Padova, Italy, 2002.
luo:cgim2002:
Alison Luo, Ahmed Amer, Newton Der, Darrell D. E. Long, and Alex Pang. Visualizing the predictability of file access patterns. In Proceedings of IASTED Computer Graphics and Imaging (CGIM), Kauai, Hawaii, 2002.
luo:sciencechina10:
MingXing Luo, YiXian Yang, LiCheng Wang, and XinXin Niu. Secure network coding in the presence of eavesdroppers. Science China: Information Sciences, 53(3):648–658, 2010.
luo:tos12:
Jianqiang Luo, Kevin D. Bowers, Alina Oprea, and Lihao Xu. Efficient software implementations of large finite fields GF($2^n$) for secure storage applications. ACM Transactions on Storage, 8(1), February 2012.
lv:eurosys06:
Qin Lv, William Josephson, Zhe Wang, Moses Charikar, and Kai Li. Ferret: a toolkit for content-based similarity search of feature-rich data. In Proceedings of EuroSys 2006, pages 317–330, April 2006.
lv:ics02:
Qin Lv, Pei Cao, Edith Cohen, Kai Li, and Scott Shenker. Search and replication in unstructured peer-to-peer networks. In Proceedings of the 16th International Conference on Supercomputing, pages 84–95, New York, NY, 2002. ACM.
lyman:info2003:
Peter Lyman, Hal R. Varian, Peter Charles, Nathan Good, Laheem Lamar Jordan, and Joyojeet Pal. How much information? 2003. http://www.sims.berkeley.edu/research/projects/how-much-info-2003/.
lynch:firstmonday01:
Clifford Lynch. The battle to define the future of the book in the digital world. First Monday, 6(6), June 2001. available at http://firstmonday.org/issues/issue6\_6/lynch/index.html.

Abstract: Commercial publishing interests are presenting the future of the book in the digital world through the promotion of e-book reading appliances and software. Implicit in this is a very complex and problematic agenda that re-establishes the book as a digital cultural artifact within a context of intellectual property rights management enforced by hardware and software systems. With the convergence of different types of content into a common digital bit-stream, developments in industries such as music are establishing precedents that may define our view of digital books. At the same time we find scholars exploring the ways in which the digital medium can enhance the traditional communication functions of the printed work, moving far beyond literal translations of the pages of printed books into the digital world. This paper examines competing visions for the future of the book in the digital environment, with particular attention to questions about the social implications of controls over intellectual property, such as continuity of cultural memory.

lynch:nature08:
Clifford Lynch. How do your data grow?. Nature, 455, September 2008.
ma:tpds00:
Gang Ma, Adnan Khaleel, and A. L. Narasimha Reddy. Performance evaluation of storage systems based on network-attached disks. IEEE Transactions on Parallel and Distributed Systems, 11(9):956–968, September 2000.
maccormick:osdi04:
John MacCormick, Nick Murphy, Marc Najork, Chandramohan A. Thekkath, and Lidong Zhou. Boxwood: Abstractions as the foundation for storage infrastructure. In Proceedings of the 6th Symposium on Operating Systems Design and Implementation (OSDI), San Francisco, CA, December 2004.
maccormick:tos09:
John MacCormick, Nicholas Murphy, Venugopalan Ramasubramanian, Udi Wieder, Junfeng Yang, and Lidong Zhou. Kinesis: A new approach to replica placement in distributed storage systems. ACM Transactions on Storage, 4(4), January 2009.
macdonald:thesis:
Joshua P. MacDonald. File system support for delta compression. Master's thesis, University of California at Berkeley, 2000.
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J. B. MacQueen. Some methods for classification and analysis of multivariate observations. In Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, volume 1, pages 281–297. University of California Press, 1967.
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madden:osdi02:
Samuel Madden, Michael J. Franklin, Joseph M. Hellerstein, and Wei Hong. TAG: A Tiny AGgregation service for ad-hoc sensor networks. In Proceedings of the 5th Symposium on Operating Systems Design and Implementation (OSDI), Boston, MA, USA, December 2002.
madhyastha:iopads97:
Tara M. Madhyastha and Daniel A. Reed. Input/output access pattern classification using hidden Markov models. In Proceedings of I/O in Parallel and Distributed Systems (IOPADS '97), pages 57–67, November 1997.
madhyastha:mss01:
Tara Madhyastha and Katherine Pu Yang. Physical modeling of probe-based storage. In Proceedings of the 18th IEEE Symposium on Mass Storage Systems and Technologies, pages 207–224, Monterey, CA, April 2001. IEEE Computer Society Press.
magoutis:usenix02:
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Keyword: parallel I/O, hypercube, Intel iPSC/2, multiprocessor file system

Comment: Intel iPSC/2 Concurrent File System. Chose to tailor system for high performance for large files, read in large chunks. Uniform logical file system view, Unix stdio interface. Blocks scattered over all disks, but not striped. Blocksize 4K optimizes message-passing performance without using blocks that are too big. Tree-directory is stored in ONE file and managed by ONE process, so opens are bottlenecked, but that is not their emphasis. File headers, however, are scattered. The file header info contains a list of blocks. File header is managed by disk process on its I/O node. Data caching is done only at the I/O node of the originating disk drive. Read-ahead is used but not detailed here.

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Abstract: In September 2001, the University of Virginia was awarded a grant from the Andrew W. Mellon Foundation to develop the first digital object repository management system based on the Flexible Extensible Digital Object and Repository Architecture (Fedora) [1]. The Digital Library Research Group at Cornell University originally developed Fedora under a National Science Foundation Grant [1-3]. Fedora is one of a number of repository architectures that have been proposed over recent years for use in digital libraries. Related architectures have included those described in Kahn and Wilensky [4], Arms, et.al. [5], Mnch [6], and Nelson and Maly [7]. The Digital Library Research and Development Department at the University of Virginia Library reinterpreted the architecture and built a prototype that demonstrated the feasibility of the architecture with their large and diverse digital collections [8]. Together, the two groups make up the development team for the project.

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Abstract: Microelectronics researchers have been investigating spin for at least 20 years. Indeed, their discoveries revolutionized hard-disk drives, which since 1998 have used a spin-based phenomenon to cram more bits than ever on to their disks. Within three years, Motorola Inc. and IBM Corp. are expected to take the next step, introducing the first commercial semiconductor chips to exploit spin-a new form of random access memory called M (for magnetic) RAM. In this paper, the author describes how the mystical property of electron spin is revolutionizing the memory business. If it can do the same with logic, electronics will become "spintronics".