The Distributed Systems (DSY) research group focuses on scalable and reliable implementation of sophisticated IT-based services. We address questions such as:
- What architecture best suits your specific cloud application?
- Which service model (IaaS, CaaS, PaaS, FaaS, ...) ensures optimal implementation of an application?
- Which tools are needed for development, operation and monitoring of the services?
- How to offer applications "as a service" (SaaS)?
- How to monetize modern IT services?
- How to integrate the "physical world" into complex IT services?
The research group is engaged in international projects within the EU research framework and works closely with partners from the private sector on innovative products within Innosuisse funded or directly financed projects.
The knowledge gained from applied research and development is transferred to students of computer science courses in the following modules:
The Init Cloud Computing Lab (ICCLAB) is dedicated to the automated deployment, operation and usage of configurable, highly scalable and resilient IT resources on a pay-per-use basis. In addition to infrastructure virtualization, this includes platform services for automated application delivery, scalable back-end, and monitoring of services and applications.
The Service Prototyping Lab (SPLAB) addresses the implementation and validation of complex services in cloud or post-cloud environments. In addition to the migration of existing services to the cloud, the main focus is on modern application architectures (Cloud Native Applications, Microservices, Serverless), the provisioning of tools for optimal implementation, the experimental validation of concepts and their monetization (Cloud Accounting and Billing).
The Init Cloud Comupting Lab (ICCLAB) also addresses the integration of robotic applications into complex networked services. The usage of elastic cloud services allows to extend the capabilities of robots (computing power, context information, artificial intelligence, ...) as well as to manage and coordinate them. Programming frameworks and automation services enable developers to integrate robots into services without having in-depth knowledge at device level.
Supporting the adoption of FAIR and reproducible digital scholarship with Renku
The goal of this project is to significantly increase the visibility of a mature solution, anticipating the adoption of Renku as a tool to improve research management in Switzerland, leveraging existing knowledge, resources and networks built in the context of past and current projects supported by ...
Smart City Simulation Platform
An IoT system consists of hundreds of thousands of sensors, connectivity media, cloud analytics, and users. Building such a large and complex IoT system such as smart-city requires careful planning, selection of the right set of hardware and software technology and development of scalable computing infrastructure ...
Application of stealth computing in highly information-sensitive cloud environments
Highly information-sensitive domains such as banking, healthcare and government services have been reluctant to adopt cloud and distributed computing technologies since their wide-spread commercial inception over the past 12 years. In contrast, many other sectors such as telecommunications and shops have embraced ...
Braschler, Martin; Stadelmann, Thilo; Stockinger, Kurt, eds.,
Applied data science : lessons learned for the data-driven business.
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