Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: Navigation; Scalable; Hierarchy. Includes bibliographical references (p. 73-77).

Thesis (M.S.)--Brigham Young University. Dept. of Computer Science, 2004. / Includes bibliographical references (p. 49-52).

Thesis (M.S.)--University of Texas at El Paso, 2009. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.

"Modern computer applications from business decision support to scientific data analysis use visualization techniques. However, visual exploration tools do not scale well for large data sets, i.e., the level of clutter on the screen is typically unacceptable. To solve the problem of cluttering at the interface level, visualization tools have recently been extended to support hierarchical views of the data, with support for focusing and drilling-down using interactive selection. To solve the scalability problem, we now investigate how best to couple such a near real-time responsive visualization tool with a database management system. Our solution proposes a framework containing three major components: hierarchy encoding, caching and prefetching. Since the direct implementation of the visual user interactions on hierarchical data sets corresponds to recursive query processing, we have developed a hierarchy encoding method, called the MinMax tree, that pushes the on-line recursive processing step into an off-line precomputation step. The MinMax encoding scheme allows us to map the hierarchy to a 2-dimensional space and the recursive navigation operations at the interface level to 2-dimensional spatial range queries. These queries can then be answered efficiently using spatial indexes. To compliment this encoding scheme we employ a caching strategy that exploits user navigation characteristics to cache the nodes having high probability of being referenced again. Based on user characteristics we choose to implement two replacement policies one which exploits temporal locality (LRU) and the other exploits spatial locality (Distance). Also, to enhance the performance of the cache we propose using a prefetching mechanism that predicts and prefetches future user requests into the cache. Together the components form a comprehensive framework that scales the visualization tool to support navigation operations over large data sets. The techniques have been incorporated into XmdvTool, a free software package for multi-variate data visualization and exploration. Our experimental results quantify the effectiveness of each component and show that collectively the components scale the XmdvTool to support navigation operations over large data sets. Mainly, our experimental results show that together the components can achieve 63\% to 96\%reduction in response time latency even with limited system resources."

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (p. 132-136).

Thesis (Ph. D.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, 2008. / Includes bibliographical references.

Redundant Arrays of Inexpensive Disks or RAID is a popular method of improving the reliability and performance of disk storage. Of various levels of RAID, mirrored or RAID1 and rotating parity or RAID5 configurations have become moat popular. Mirrored or RAID1 provides best overall performance and is easier to configure, but has 100 percent storage overhead for the redundancy. Rotating parity or RAID5, on the other hand, is quite inexpensive for the redundancy it provides, shorn impressive performance for reads and full-stripe writes in normal mode, but the small write performance is poor due to the read-modify-write cycle involved. The performance drops drastically when one of the disks fails and the system enters degraded mode. Also RAID5 is relatively difficult to configure. Typical non-scientific system disk access patterns exhibit very high locality of reference. This thesis presents the design and implementation of an Adaptive Hierarchical RAID array to exploit this high locality. Frequently accessed data is migrated towards the top of the hierarchy and not so frequently acee88ed data is moved down the hierarchy, thus adaptively rearranging itself to the access patterns. Previous work on Adaptive Hierarchical RAID such as HP AutoRAID has explored one part of the design space, namely design of configurable storage at the SGSI level with no interaction with higher level layers like volume manager. This thesis explores a different design point: namely, one that is centered at the volume manager layer. This is important also for the reason that with fibre channel disks and SCSI-3, Storage Area Networks (SAN) no longer need a conventional controller but a modified version of a controller that is more close to a volume manager.

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