The Multiscale Networked System (MNS) group researches the emerging architectures that can support the operations of multiscale systems across the Future Internet.
Software tools, infrastructures, and demonstrations are, just as scientific publications, considered to be important research output of the MNS group. Over the years, the researchers and PhD-students of the MNS group developed several research tools and infrastructures.
The Dynamic Real-time Infrastructure Planner (DRIP) is a microservice suite for planning and provisioning networked virtual machines, for deploying application components and for managing runtime infrastructures based on time-critical constraints.
The intuition our group had years ago was that we could leverage Semantic Web technologies to identify the exchangeable knowledge required to federate networks. We proved that we can manage the complexity and heterogeneity of the Internet with semantically rich models.
Large OBject Cloud Data storagE fedeRation (LOBCDER) is a data management system that federates storage resources. It is a part of the Data and Compute Cloud Platform4 of the VPH-Share project.
Pumpkin is a framework for distributed Data Transformation Network developed in the COMMIT Project. It implements a protocol for distributed data processing. A data packet is a self-contained processing unit, which incorporates data, state, code and routing information.
This video shows a screencapture of the SARNET demonstration at SC16. The demo shows a virtual network that leverages Software Defined Networks and Network
WeevilScout. Given the ubiquity of Web browsers and the performance gains being achieved by JavaScript virtual machines, a question arises: Could Internet browsers become yet another middleware for distributed computing?
The OpenLab facility is managed by the MNS group and available to all researchers within the SNE cluster and the associated educational programs, e.g. Software Engineering (SE) and Security and Network Engineering (SNE) masters.
It is designed to support research and experimentation in software defined networking, embedded systems, distributed systems, Future Internet architectures and protocols, and secure data sharing platforms, and evaluate the applicability of Machine Learning in those research domains.
Learn more about the OpenLab here.