Advanced data deduplication techniques and their application

Data deduplication describes a class of approaches that reduce the storage capacity needed to store data or the amount of data that has to be transferred over a network. These approaches detect coarse-grained redundancies within a data set, e.g. a file system, and remove them.rnrnOne of the most important applications of data deduplication are backup storage systems where these approaches are able to reduce the storage requirements to a small fraction of the logical backup data size.rnThis thesis introduces multiple new extensions of so-called fingerprinting-based data deduplication. It starts with the presentation of a novel system design, which allows using a cluster of servers to perform exact data deduplication with small chunks in a scalable way.rnrnAfterwards, a combination of compression approaches for an important, but often over- looked, data structure in data deduplication systems, so called block and file recipes, is introduced. Using these compression approaches that exploit unique properties of data deduplication systems, the size of these recipes can be reduced by more than 92% in all investigated data sets. As file recipes can occupy a significant fraction of the overall storage capacity of data deduplication systems, the compression enables significant savings.rnrnA technique to increase the write throughput of data deduplication systems, based on the aforementioned block and file recipes, is introduced next. The novel Block Locality Caching (BLC) uses properties of block and file recipes to overcome the chunk lookup disk bottleneck of data deduplication systems. This chunk lookup disk bottleneck either limits the scalability or the throughput of data deduplication systems. The presented BLC overcomes the disk bottleneck more efficiently than existing approaches. Furthermore, it is shown that it is less prone to aging effects.rnrnFinally, it is investigated if large HPC storage systems inhibit redundancies that can be found by fingerprinting-based data deduplication. Over 3 PB of HPC storage data from different data sets have been analyzed. In most data sets, between 20 and 30% of the data can be classified as redundant. According to these results, future work in HPC storage systems should further investigate how data deduplication can be integrated into future HPC storage systems.rnrnThis thesis presents important novel work in different area of data deduplication re- search.

Strukturen und Phasen des beta-Eukryptits sowie die Sammlung von Beugungsdaten mit axialen q-Scans

Der 'gestopfte Hochquarz' ß-Eukryptit (LiAlSiO4) ist bekannt für seine außergewöhnliche anisotrope Li-Ionenleitfähigkeit und die nahe Null liegende thermische Ausdehnung.Untersucht wurde die temperaturabhängige ß-Eukryptit-Phasenabfolge, insbesondere die modulierte Phase. Deren Satellitenreflexe sind gegenüber den normalen Reflexen erheblich verbreitert, überlappen miteinander sowie mit den dazwischen liegenden 'a-Reflexen' zu Tripletts. Für die Separation der Triplett-Intensitäten waren bisherige Standardverfahren zur Beugungsdatensammlung ungeeignet. Mit 'axialen q-Scans' wurde ein neuartiges Verfahren entwickelt. Intensitäten wurden mit dem neu-entwickelten least squares-Programm GKLS aus 2000 Profilen seriell und automatisch gewonnen und erfolgreich auf Standarddaten skaliert. Die Verwendung verbreiterter Reflexprofile erwies sich als zulässig.Die Verbreiterung wurde auf eine verminderte Fernordnung der Modulation von 11 bis 16 Perioden zurückgeführt (Analyse mit der Gitterfunktion), womit ein ungewöhnliches beugungswinkelabhängiges Verhalten der Reflexbreiten korrespondiert und mit typischen Antiphasendomänendurchmessern (andere Autoren) korreliert.Eine verminderte Si-/ Al-Ordnung wird als ursächlich für geringe Domänengrößen und Fernordnung angesehen, sowie für Eigenschaften wie z.B. a/c-Verhältnisse, Ausdehnungskoeffizienten, Ionenleitfähigkeit, Strukturtyp und Umwandlungstemperaturen. Änderungen des SiO2-Gehaltes, der Temperatur oder der Si- /Al-Ordnung zeitigen für einige Eigenschaften ähnliche Wirkungen.Die gemittelte Struktur der modulierten Phase wurde erstmals zuverlässig bestimmt, die Rolle des Li charakterisiert, Zweifel an der hexagonalen Symmetrie des ß-Eukryptits wurden ausgeräumt und die Bestimmung der modulierten Struktur wurde weitgehend vorbereitet.

Software tools and efficient algorithms for the feature detection, feature tracking, event localization, and visualization of large sets of atmospheric data

Data sets describing the state of the earth's atmosphere are of great importance in the atmospheric sciences. Over the last decades, the quality and sheer amount of the available data increased significantly, resulting in a rising demand for new tools capable of handling and analysing these large, multidimensional sets of atmospheric data. The interdisciplinary work presented in this thesis covers the development and the application of practical software tools and efficient algorithms from the field of computer science, aiming at the goal of enabling atmospheric scientists to analyse and to gain new insights from these large data sets. For this purpose, our tools combine novel techniques with well-established methods from different areas such as scientific visualization and data segmentation. In this thesis, three practical tools are presented. Two of these tools are software systems (Insight and IWAL) for different types of processing and interactive visualization of data, the third tool is an efficient algorithm for data segmentation implemented as part of Insight.Insight is a toolkit for the interactive, three-dimensional visualization and processing of large sets of atmospheric data, originally developed as a testing environment for the novel segmentation algorithm. It provides a dynamic system for combining at runtime data from different sources, a variety of different data processing algorithms, and several visualization techniques. Its modular architecture and flexible scripting support led to additional applications of the software, from which two examples are presented: the usage of Insight as a WMS (web map service) server, and the automatic production of a sequence of images for the visualization of cyclone simulations. The core application of Insight is the provision of the novel segmentation algorithm for the efficient detection and tracking of 3D features in large sets of atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. Data segmentation usually leads to a significant reduction of the size of the considered data. This enables a practical visualization of the data, statistical analyses of the features and their events, and the manual or automatic detection of interesting situations for subsequent detailed investigation. The concepts of the novel algorithm, its technical realization, and several extensions for avoiding under- and over-segmentation are discussed. As example applications, this thesis covers the setup and the results of the segmentation of upper-tropospheric jet streams and cyclones as full 3D objects. Finally, IWAL is presented, which is a web application for providing an easy interactive access to meteorological data visualizations, primarily aimed at students. As a web application, the needs to retrieve all input data sets and to install and handle complex visualization tools on a local machine are avoided. The main challenge in the provision of customizable visualizations to large numbers of simultaneous users was to find an acceptable trade-off between the available visualization options and the performance of the application. Besides the implementational details, benchmarks and the results of a user survey are presented.