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Auflistung nach Autor:in "Brunnert, Andreas"

1 - 5 von 5
  • Konferenzbeitrag
    Model-based Energy Consumption Prediction for Mobile Application
    (Proceedings of the 28th Conference on Environmental Informatics - Informatics for Environmental Protection, Sustainable Development and Risk Management, 2014) Willnecker, Felix; Brunnert, Andreas; Krcmar, Helmut
    Investigating the energy consumption of mobile applications (apps) is becoming a growing software engineering challenge due to the limited battery lifetime of mobile devices. Energy consumption is defined as the power demand integrated over time. Profiling the power demand of an app is a time consuming activity and the results are only valid for the target hardware used during the measurements. The energy consumption is influenced by the resource demands of an app, the hardware on which the app is running, and its workload. This work adapts resource profiles for enterprise applications to predict the energy consumption of mobile apps without the need to own a physical device. Resource profiles are models that represent all aspects influencing the energy consumption of an app. They can be used to predict the energy consumption for different hardware devices and evaluate the overall efficiency of an app. Moreover, the workload can be changed so that the impact of different usage patterns can be investigated. These capabilities lay the foundation for a platform-independent way of quantifying the energy consumption of mobile apps
  • Zeitschriftenartikel
    Modeling Big Data Systems by Extending the Palladio Component Model
    (Softwaretechnik-Trends Band 35, Heft 3, 2015) Kroß, Johannes; Brunnert, Andreas; Krcmar, Helmut
    The growing availability of big data has induced new storing and processing techniques implemented in big data systems such as Apache Hadoop or Apache Spark. With increased implementations of these systems in organizations, simultaneously, the requirements regarding performance qualities such as response time, throughput, and resource utilization increase to create added value. Guaranteeing these performance requirements as well as efficiently planning needed capacities in advance is an enormous challenge. Performance models such as the Palladio component model (PCM) allow for addressing such problems. Therefore, we propose a metamodel extension for PCM to be able to model typical characteristics of big data systems. The extension consists of two parts. First, the meta-model is extended to support parallel computing by forking an operation multiple times on a computer cluster as intended by the single instruction, multiple data (SIMD) architecture. Second, modeling of computer clusters is integrated into the meta-model so operations can be properly scheduled on contained computing nodes.
  • Zeitschriftenartikel
    Performance Management Work
    (Wirtschaftsinformatik: Vol. 56, No. 3, 2014) Brunnert, Andreas; Vögele, Christian; Danciu, Alexandru; Pfaff, Matthias; Mayer, Manuel; Krcmar, Helmut
  • Zeitschriftenartikel
    A Performance Model Management Repository Based on the Palladio Component Model
    (Softwaretechnik-Trends Band 35, Heft 3, 2015) Danciu, Alexandru; Brunnert, Andreas; Krcmar, Helmut
    Applying performance models to evaluate component-based enterprise applications in practice is becoming more and more difficult with an increasing organizational complexity. Components can be governed by different organizational units, are subject to a continuous shift between life cycle phases, and exhibit diverging release levels. Creating and maintaining performance models based on the composition of these components can, therefore, represent an elaborate task. A Performance Model Management Repository (PMMR) supports managing performance models in complex enterprise environments. This paper presents the implementation of a PMMR based on the Palladio Component Model (PCM). The PCM meta-model is extended to enable managing and maintaining multiple versions of components and their interfaces. Furthermore, resource demand specifications derived from different hardware environments are integrated into the meta-model. The Palladio-Bench is extended for persisting PMMR elements to EMFStore.
  • Zeitschriftenartikel
    Symposium on Software Performance (SSP) 2015
    (Softwaretechnik-Trends Band 35, Heft 3, 2015) Becker, Steffen; Brunnert, Andreas; Hasselbring, Wilhelm; van Hoorn, André; Kounev, Samuel; Krcmar, Helmut; Reussner, Ralf