CloudStars is an Open Source Research Mobility network in the field of Cloud Computing technology. The proposal combines eleven academic institutions in nine European countries (Spain, Portugal, UK, Germany, Netherlands, Italy, Au...
CloudStars is an Open Source Research Mobility network in the field of Cloud Computing technology. The proposal combines eleven academic institutions in nine European countries (Spain, Portugal, UK, Germany, Netherlands, Italy, Austria, Poland, Switzerland), two companies in Europe (SAP in Germany, NearBy Computing in Spain), and three industrial laboratories from IBM (USA, Switzerland, and Israel). The major flow of secondments is scheduled between the academic institutions and IBM industrial labs, but also including a significant number of secondments to SAP and NearBy Computing.
CloudStars will create a global reference community in open source Cloud Computing. The participants will combine theoretical skills and
experience in distributed systems research with industrial open source technologies and cutting-edge Cloud and Edge infrastructures. This will increase the overall global impact of research contributions, helping to arrive to millions of interested third parties through open source communities.
The general goals of the project are:
1. Increase the impact of European researchers with contributions to key open source projects and the involvement in open source communities.
2. Rise the careers of European researchers through well-established networks both across EU and with global open source players.
3. Increase the reproducibility of results in Science and Data Analytics through standard Cloud container technologies.
Technical goals are:
1. Development and benchmarking of next generation container technologies leveraging open source Cloud Native Computing Foundation (CNCF) projects and GAIAX protocols.
2. Design novel cloud serverless middleware over container technologies including Function as a Service, serverless containers, and event-based orchestration.
3. Apply novel machine learning techniques for managing containerized Cloud and Edge systems, involving the infrastructure and configuration of executions and services.ver más
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