Research Interests

  • Database Technology
    • Data management on modern hardware
      • Co-processor-accelerated query optimization
      • Efficient algorithms for query (co-)processing on heterogeneous hardware (e.g., GPUs, Intel Xeon Phi, NUMA Systems)
      • Genome data analysis using main-memory databases
      • Multi-dimensional index structures for main-memory databases
    • Graph database management systems
    • Large-scale and cloud data management
      • NoSQL databases
      • Transaction management in the cloud
      • Data integrity in the cloud
      • Parallel entity resolution
      • Self-tuning for cloud storage clusters
  • Feature-Oriented Software Development (FOSD)
    • Product-line configuration recommender systems
    • Prioritization for software product line testing
    • Migration of cloned product variants to a software product line
    • Variability-aware refactoring
    • Variability-aware code smells
    • Formal specification and verification of software product lines
    • Analysis of variability models
    • Multi software product lines
  • Variability in Embedded Systems / Heterogenous Hardware
    • Composition and adaptation of software product lines at runtime
    • Syntactical and semanticle interoperability in heterogeneous (embedded) systems
    • Data management in embedded systems and sensor networks

Current Funded Projects

Other Research Projects

  • Modern Data Management Technologies for Genome Analysis
  • Software Product Line Languages and Tools (FeatureIDE, SPL2go)
  • Load-balanced Index Structures for Self-tuning DBMS
  • Model-Based Refinement of Product Lines
  • GPU-accelerated Join-Order Optimization
  • On the Impact of Hardware on Relational Query Processing
  • On the Impact of Hardware on Relational Query Processing

    Satisfying the performance needs of tomorrow typically implies using modern processor capabilities (such as single instruction, multiple data) and co-processors (such as graphics processing units) to accelerate database operations. Algorithms are typically hand-tuned to the underlying (co-)processors. This solution is error-prone, introduces high implementation and maintenance cost and is not portable to other (co-)processors. To this end, we argue for a combination of database research with modern software-engineering approaches, such as feature-oriented software development (FOSD). Thus, the goal of this project is to generate optimized database algorithms tailored to the underlying (co-)processors from a common code base. With this, we maximize performance while minimizing implementation and maintenance effort in databases on new hardware.

    Project milestones:

    • Creating a feature model: Arising from heterogeneous processor capabilities, promising capabilities have to be identified and structured to develop a comprehensive feature model. This includes fine-grained features that exploit the processor capabilities of each device.
    • Annotative vs. compositional FOSD approaches: Both approaches have known benefits and drawbacks. To have a suitable mechanism to construct hardware-tailored database algorithms using FOSD, we have to evaluate which of these two approaches is the best for our scenario.
    • Mapping features to code: Arising from the feature model, possible code snippets to implement a feature have to be identified.
    • Performance evaluation: To validate our solution and derive rules for processor allocation and algorithm selection, we have to perform an evaluation of our algorithms.

    Leader:Prof. Dr. Gunter Saake
    Members:David Broneske
    Funded by:Haushalt
    Keywords:heterogeneity of processing devices, CPU, GPU, FPGA, MIC, APU, tailored database operations
  • Variability in service-oriented computing
  • Reliable and Reproducible Evaluation of High-Dimensional Index Structures (QuEval)

Completed Projects

Past Conference

Database Systems for Business, Technology, and Web (BTW)

The 15th BTW conference on "Database Systems for Business, Technology, and Web" (BTW 2013) of the Gesellschaft für Informatik (GI) will take place from March 11th to March 15th, 2013 at the Otto-von-Guericke-University of Magdeburg, Germany.


Past Workshops