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Auflistung nach Autor:in "Schintke, Florian"

1 - 5 von 5
  • Konferenzbeitrag
    Dienste und Standards für das Grid Computing
    (E-Science und Grid Ad-hoc Netze Medienintegration, 18. DFN-Arbeitstagung über Kommunikationsnetze, 2004) Reinefeld, Alexander; Schintke, Florian
    In der noch jungen Geschichte des Grid Computing wurden bereits mehrere Standards für serviceorientierte Grids vorgeschlagen und diskutiert: OGSA, OGSI und WSRF, sowie Grid-spezifische Erweiterungen der Web Services. Sie alle haben das Ziel, zustandsbehaftete, transiente Dienste zur kooperativen Nutzung im Grid freizugeben. Ortstransparenz wird durch Virtualisierung ermöglicht: Nicht der interne Aufbau oder gar die Implementation eines Dienstes stehen im Vordergrund, sondern die Definition der Schnittstellen und Protokolle, über die der Dienst angesprochen werden kann. Dieser Artikel soll das gewachsene und scheinbar undurchdringliche Dickicht der verschiedenen Grid-Architekturen und -Standards etwas lichten und auf diese Weise zu einem besseren Verständnis der wichtigsten Konzepte des Grid Computing sowie ihrer Hintergründe beitragen.
  • Zeitschriftenartikel
    Grid Services
    (Informatik-Spektrum: Vol. 27, No. 2, 2004) Reinefeld, Alexander; Schintke, Florian
    Grid Computing nutzt eine Erweiterung der Web Services, um in einer offenen Grid- Architektur Standarddienste und -verhalten zu definieren.
  • Zeitschriftenartikel
    Handling Big Data in Astronomy and Astrophysics: Rich Structured Queries on Replicated Cloud Data with XtreemFS
    (Datenbank-Spektrum: Vol. 12, No. 3, 2012) Enke, Harry; Partl, Adrian; Reinefeld, Alexander; Schintke, Florian
    With recent observational instruments and survey campaigns in astrophysics, efficient analysis of big structured data becomes more and more relevant. While providing good query expressiveness and data analysis capabilities through SQL, off-the-shelf RDBMS are yet not well prepared to handle high volume scientific data distributed across several nodes, neither for fast data ingest nor for fast spatial queries. Our SQL query parser and job manager performs query reformulation to spread queries to data nodes, gathering outputs on a head node and providing them again to the shards for subsequent processing steps. We combine this data analysis architecture with the cloud data storage component XtreemFS for automatic data replication to improve the availability and access latency. With our solution we perform rich structured data analysis expressed using SQL on large amounts of structured astrophysical data distributed across numerous storage nodes in parallel. The cloud storage virtualization with XtreemFS provides elasticity and reproducibility of scientific analysis tasks through its snapshot capability.
  • Zeitschriftenartikel
    The Collaborative Research Center FONDA
    (Datenbank-Spektrum: Vol. 21, No. 3, 2021) Leser, Ulf; Hilbrich, Marcus; Draxl, Claudia; Eisert, Peter; Grunske, Lars; Hostert, Patrick; Kainmüller, Dagmar; Kao, Odej; Kehr, Birte; Kehrer, Timo; Koch, Christoph; Markl, Volker; Meyerhenke, Henning; Rabl, Tilmann; Reinefeld, Alexander; Reinert, Knut; Ritter, Kerstin; Scheuermann, Björn; Schintke, Florian; Schweikardt, Nicole; Weidlich, Matthias
    Today’s scientific data analysis very often requires complex Data Analysis Workflows (DAWs) executed over distributed computational infrastructures, e.g., clusters. Much research effort is devoted to the tuning and performance optimization of specific workflows for specific clusters. However, an arguably even more important problem for accelerating research is the reduction of development, adaptation, and maintenance times of DAWs. We describe the design and setup of the Collaborative Research Center (CRC) 1404 “FONDA -– Foundations of Workflows for Large-Scale Scientific Data Analysis”, in which roughly 50 researchers jointly investigate new technologies, algorithms, and models to increase the portability, adaptability, and dependability of DAWs executed over distributed infrastructures. We describe the motivation behind our project, explain its underlying core concepts, introduce FONDA’s internal structure, and sketch our vision for the future of workflow-based scientific data analysis. We also describe some lessons learned during the “making of” a CRC in Computer Science with strong interdisciplinary components, with the aim to foster similar endeavors.
  • Zeitschriftenartikel
    Towards Log-Less, Fine-Granular State Machine Replication
    (Datenbank-Spektrum: Vol. 20, No. 3, 2020) Skrzypzcak, Jan; Schintke, Florian
    State machine replication is used to increase the availability of a service such as a data management system while ensuring consistent access to it. State-of-the-art implementations are based on a command log to gain linear write access to storage and avoid repeated transmissions of large replicas. However, the command log requires non-trivial state management such as allocation and pruning to prevent unbounded growth. By introducing in-place replicated state machines that do not use command logs, the log overhead can be avoided. Instead, replicas agree on a sequence of states, and former states are directly overwritten. This method enables the consistent, fault-tolerant replication of basic data management primitives such as counters, sets, or individual locks with little to no overhead. It matches the properties of fast, byte-addressable, non-volatile memory particularly well, where it is no longer necessary to rely on sequential access for good performance. Our approach is especially well suited for small states and fine-granular distributed data management as it occurs in key-value stores, for example.