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The transfer of historically grown monolithic software architectures into modern service-oriented architectures creates a lot of loose coupling points. This can lead to an unforeseen system behavior and can significantly impede those continuous modernization processes, since it is not clear where bottlenecks in a system arise. It is therefore necessary to monitor such modernization processes with an adaptive monitoring concept to be able to correctly record and interpret unpredictable system dynamics. This contribution presents a generic QoS measurement framework for service-based systems. The framework consists of an XML-based specification for the measurement to be performed – the Information Model (IM) – and the QoS System, which provides an execution platform for the IM. The framework will be applied to a standard business process of the German insurance industry, and the concepts of the IM and their mapping to artifacts of the QoS System will be presented. Furtherm ore, design and implementation of the QoS System’s parser and generator module and the generated artifacts are explained in detail, e.g., event model, agents, measurement module and analyzer module.
The transfer of historically grown monolithic software architectures into modern service-oriented architectures creates a lot of loose coupling points. This can lead to an unforeseen system behavior and can significantly impede those continuous modernization processes, since it is not clear where bottlenecks in a system arise. It is therefore necessary to monitor such modernization processes with an adaptive monitoring concept in order to be able to correctly record and interpret unpredictable system dynamics. For this purpose, a general measurement methodology and a specific implementation concept are presented in this work.
In the context of modern mobility, topics such as smart-cities, Car2Car-Communication, extensive vehicle sensor-data, e-mobility and charging point management systems have to be considered. These topics of modern mobility often have in common that they are characterized by complex and extensive data situations. Vehicle position data, sensor data or vehicle communication data must be preprocessed, aggregated and analyzed. In many cases, the data is interdependent. For example, the vehicle position data of electric vehicles and surrounding charging points have a dependence on one another and characterize a competition situation between the vehicles. In the case of Car2Car-Communication, the positions of the vehicles must also be viewed in relation to each other. The data are dependent on each other and will influence the ability to establish a communication. This dependency can provoke very complex and large data situations, which can no longer be treated efficiently. With this work, a model is presented in order to be able to map such typical data situations with a strong dependency of the data among each other. Microservices can help reduce complexity.
