A5075247619- Service-Oriented Architecture and Web Services
- Advanced Software Engineering Methodologies
- Neural Networks and Applications
- Software System Performance and Reliability
- Scientific Computing and Data Management
- Model-Driven Software Engineering Techniques
- Cloud Computing and Resource Management
- Real-Time Systems Scheduling
- Business Process Modeling and Analysis
- Advanced Memory and Neural Computing
- IoT and Edge/Fog Computing
- Semantic Web and Ontologies
- Manufacturing Process and Optimization
University of Stuttgart
2022-2024
The manual deployment of applications distributed across the cloud, fog, and edge is error-prone complex. TOSCA a standard for modeling cloud in vendor-neutral technology-independent manner that also suitable fog continuum. However, there exist various orchestrators with different functionalities. Thus, selecting an appropriate orchestrator requires technical expertise since all available must be analyzed regarding technical, functional, legal, organizational requirements. In this paper, we...
Infrastructure-as-Code (IaC) technologies are used to automate the deployment of cloud applications. They promote usage code define and configure IT infrastructure applications allowing them benefit from conventional software development practices, which facilitates rapid new versions application infrastructures without sacrificing quality or stability. On other hand, enterprise need conform compliance regarding external regulations internal policies. Many these rules affect architecture on...
For automating the deployment of composite applications, typically, declarative models are used. Depending on context, an application has to fulfill different requirements, such as costs and elasticity. As a consequence, one same application, i.e., its components, their dependencies, often need be deployed in variants. If each variant is described using individual model, it quickly results large number models, which error prone maintain. Deployment technologies, Terraform or Ansible, support...
Since applications often need to be deployed in different variants, deployment technologies, such as Ansible and Terraform, support modeling variability. Unfortunately, typically the combination of multiple which have proprietary non-interoperable variability concepts. Therefore, variable models been introduced model across technologies by assigning conditions elements specify their presence. However, manual these is repetitive, error-prone, time-consuming. In this paper, we propose reduce...