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Upcoming AI-based and 5G applications are demanding new network management approaches that are capable to cope with unprecedented levels of flexibility, scalability and energy efficiency. In order to make these use cases tangible and feasible, network management solutions aim to rely on multi-domain, multi-tier architectures that permit complex end-to-end orchestration of network resources. However, current research on scheduling functions and task-offloading algorithms often focus on one single-domain, and the exploration of large-scale inter-operable solutions becomes a challenge. Fortunately for the networking research community, a number of available testing facilities deployed at different geographical location along the world can be integrated to be used as a single joint multi-domain infrastructure. In this demo paper, we present a hands-off experience of how to integrate different high-performance testbeds, located in USA, Belgium and The Netherlands, in order to enable multi-domain large-scale experimentation. We demonstrate end-to-end performance characteristics of the testbed integration and we describe the main takeaways and lessons learned to drive researchers towards successful deployments in such end-to-end global infrastructure. 

The Chameleon project developed a unique experimental testbed by adapting a mainstream cloud implementation to the needs of systems research community and thereby demonstrated that clouds can be configured to serve as a platform for this type research. More recently, the CloudBank project embarked on a mission of providing a conduit to commercial clouds for the systems research community that eliminates much of the complexity and some of the cost of using them for research. This creates an opportunity to explore running systems experiments in a combined setting, spanning both research and commercial clouds. In this paper, we present an extension to Chameleon for constructing controlled experiments across its resources and commercial clouds accessible via CloudBank, present a case study of an experiment running across such combined resources, and discuss the impact of using a combined research platform.