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Datenbank Spektrum 15(2) - Juli 2015

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  • Zeitschriftenartikel
    Optimized P2P Data Management for ReliableWorkflow Execution in Mobile Environments
    (Datenbank-Spektrum: Vol. 15, No. 2, 2015) Stojnić, Nenad; Schuldt, Heiko
    Workflows allow to build complex applications out of existing services. Hence, workflows are inherently distributed. At the same time, workflows are mostly executed by centralized workflow engines that invoke the services of a workflow in a request/reply style. These engines may become a performance bottleneck and limit the scalability of the entire system. As a consequence, approaches to distributed workflow execution have been proposed. While these approaches have better scalability characteristics, they require additional efforts to deal with (partial) failures of the system. To cope with such failures, workflow instance data must be stored redundantly at different sites. This is even more important in mobile environments or mixed mobile/stationary environments where the nodes hosting services for workflows may be mobile and are thus more likely to fail permanently or become temporarily unavailable. This is the case, for instance, for sensor net applications where mobile devices capture data, or when smartphone apps share and jointly process data.In this paper, we present the combination of OSIRIS-SR, an extension to the distributed and decentralized workflow engine OSIRIS that focuses on reliable workflow execution by means of instance data replication, and Compass, an extension to Chord that is particularly tailored for efficient P2P data management on mobile devices.
  • Zeitschriftenartikel
    (Datenbank-Spektrum: Vol. 15, No. 2, 2015)
  • Zeitschriftenartikel
    Toward GPU-accelerated Database Optimization
    (Datenbank-Spektrum: Vol. 15, No. 2, 2015) Meister, Andreas; Breß, Sebastian; Saake, Gunter
    For over three decades, research investigates optimization options in DBMSs. Nowadays, the hardware used in DBMSs become more and more heterogeneous, because processors are bound by a fixed energy budget leading to increased parallelism. Existing optimization approaches in DBMSs do not exploit parallelism for a single optimization task and, hence, can only benefit from the parallelism offered by current hardware by batch-processing multiple optimization tasks.Since a large optimization space often allows us to process sub-spaces in parallel, we expect large gains in result quality for optimization approaches in DBMSs and, hence, performance for query processing on modern (co-)processors. However, parallel optimization on CPUs is likely to slow down query processing, because DBMSs can fully exploit the CPUs computing resources due to high data parallelism. In contrast, the communication overhead of co-processors such as GPUs typically lead to plenty of compute resources unused.In this paper, we motivate the use of parallel co-processors for optimization in DBMSs, identify optimization problems benefiting from parallelization, and show how we can design parallel optimization approaches on the example of the operator placement problem.
  • Zeitschriftenartikel
    Der Secure Data Container (SDC)
    (Datenbank-Spektrum: Vol. 15, No. 2, 2015) Stach, Christoph; Mitschang, Bernhard
    Mobile Endgeräte wurden zu Marc Weisers Computer des 21. Jahrhunderts, da sie als dauerhaft verfügbare Informationsquelle Einzug in unseren Alltag gehalten haben. Auf ihnen treffen private Daten (z. B. Fotos) auf Kontextdaten (z. B. Standortdaten); verknüpft stellen diese ein immenses Sicherheitsrisiko dar. Wie eine Vielzahl an Datendiebstählen belegt, reichen die existierenden Datensicherheitssysteme für Mobilplattformen bei weitem nicht aus. Daher bedarf es einer Identifikation möglicher Angriffsvektoren sowie einer Analyse der speziellen Schutzziele eines solchen Systems. Darauf basierend wird die Privacy Management Platform, ein Berechtigungssystem, mithilfe des neu eingeführten Secure Data Containers zu einem ganzheitlichen Datensicherheitssystem erweitert. Dabei zeigt sich, dass diese Kombination alle Schutzziele erfüllt und dennoch hochperformant ist. Obwohl die vorgestellten Prototypen auf Android basieren, ist das Konzept auch auf andere App-Plattformen anwendbar.
  • Zeitschriftenartikel
    (Datenbank-Spektrum: Vol. 15, No. 2, 2015) Mitschang, Bernhard; Nicklas, Daniela; Härder, Theo
  • Zeitschriftenartikel
    (Datenbank-Spektrum: Vol. 15, No. 2, 2015)
  • Zeitschriftenartikel
    Managed Query Processing within the SAP HANA Database Platform
    (Datenbank-Spektrum: Vol. 15, No. 2, 2015) May, Norman; Böhm, Alexander; Block, Meinolf; Lehner, Wolfgang
    The SAP HANA database extends the scope of traditional database engines as it supports data models beyond regular tables, e.g. text, graphs or hierarchies. Moreover, SAP HANA also provides developers with a more fine-grained control to define their database application logic, e.g. exposing specific operators which are difficult to express in SQL. Finally, the SAP HANA database implements efficient communication to dedicated client applications using more effective communication mechanisms than available with standard interfaces like JDBC or ODBC. These features of the HANA database are complemented by the extended scripting engine–an application server for server-side JavaScript applications–that is tightly integrated into the query processing and application lifecycle management. As a result, the HANA platform offers more concise models and code for working with the HANA platform and provides superior runtime performance.This paper describes how these specific capabilities of the HANA platform can be consumed and gives a holistic overview of the HANA platform starting from query modeling, to the deployment, and efficient execution. As a distinctive feature, the HANA platform integrates most steps of the application lifecycle, and thus makes sure that all relevant artifacts stay consistent whenever they are modified. The HANA platform also covers transport facilities to deploy and undeploy applications in a complex system landscape.
  • Zeitschriftenartikel
    Complex Event Processing on Linked Stream Data
    (Datenbank-Spektrum: Vol. 15, No. 2, 2015) Saleh, Omran; Hagedorn, Stefan; Sattler, Kai-Uwe
    Social networks and Sensor Web technologies typically generate a massive amount of data published as streams. In order to give these streams a meaningful sense and enrich them with semantic descriptions, the concept of Linked Stream Data (LSD) has emerged. However, to support a wide range of LSD scenarios and queries comprehensive solutions providing not only classic data stream operators such as windows, but also for processing of complex events, linking of (static) datasets, and scalable processing are required. In this paper, we present our approach for processing LSD and addressing these requirements. In contrast to existing LSD engines relying on streaming extensions to SPARQL, our PipeFlow system is a (relational) dataflow language and engine providing support for complex event processing (CEP) and a few dedicated operators for RDF data. We describe this language and particularly the CEP model as well as the system architecture for parallel CEP and LSD processing by exploiting partitioning techniques for cluster environments. Finally, we report results from experiments evaluating our system in comparison to existing LSD engines.
  • Zeitschriftenartikel
    BTW 2015 – Jubiläum an der Waterkant
    (Datenbank-Spektrum: Vol. 15, No. 2, 2015) Wingerath, Wolfram; Friedrich, Steffen; Ritter, Norbert
  • Zeitschriftenartikel
    Der Lehrstuhl Datenbank- und Informationssysteme der Universität Rostock
    (Datenbank-Spektrum: Vol. 15, No. 2, 2015) Heuer, Andreas; Meyer, Holger; Bruder, Ilvio; Klettke, Meike