Christian Stier

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Design-time quality analysis of software architectures evaluates the impact of design decisions in quality dimensions such as performance. Architectural design decisions decisively impact the energy efficiency (EE) of software systems. Low EE not only results in higher operational cost due to power consumption. It indirectly necessitates additional capacity(More)
Recent advances in hardware development coupled with the rapid adoption and broad applicability of cloud computing have introduced widespread heterogeneity in data centers, significantly complicating the management of cloud applications and data center resources. This paper presents the CACTOS approach to cloud infrastructure automation and optimization,(More)
Today’s system developers and operators face the challenge of creating software systems that make efficient use of dynamically allocated resources under highly variable and dynamic load profiles, while at the same time delivering reliable performance. Autonomic controllers, for example, an advanced autoscaling mechanism in a cloud computing context,(More)
Architecture-level evaluations of Palladio currently lack support for the analysis of the power efficiency of software systems and the effect of power management techniques on other quality characteristics. This neglects that the power consumption of software systems constitutes a substantial proportion of their total cost of ownership. Currently, reasoning(More)
Providing users with Quality of Service (QoS) guarantees and the prevention of performance problems are challenging tasks for software systems. Architectural performance models can be applied to explore performance properties of a software system at design time and run time. At design time, architectural performance models support reasoning on effects of(More)
Databases are the origin of many performance problems found in transactional information systems. Performance suffers especially when databases employ locking to isolate concurrent transactions. Software performance models therefore need to reflect lock contention in order to be a credible source for guiding design decisions. We propose a hybrid simulation(More)
Model-driven performance engineering allows software architects to reason on performance characteristics of a software system in early design phases. In recent years, model-driven analysis techniques have been developed to evaluate performance characteristics of self-adaptive software systems. These techniques aim to reason on the ability of a self-adaptive(More)
In Infrastructure as a Service (IaaS) Cloud scenarios, data center operators require specifications of Virtual Machine (VM) behavior for data center middleand long-term planning and optimization. The planning is usually supported by simulations. While users can leverage white-box application knowledge, data center operators have to rely on metrics at the(More)
Model-based Quality of Service (QoS) prediction approaches enable an early identification of bottlenecks in the design of complex software systems. In addition, they allow software architects to evaluate design decisions against each other. In data-intensive business applications, database accesses have a significant impact on a system’s QoS. Therefore,(More)