For more than ten years, the Network Research and Infrastructure Group (NRIG) at RENCI has been developing specialized cyberinfrastructure critical for advancing computer science and a variety of scientific domains. Their projects are helping scientists use large amounts of data to make new discoveries and have enabled important new advances in distributing computing networks, cloud-based systems, and software-defined networks.

Next-generation testbeds

Thousands of computer scientists around the world use the cyberinfrastructure testbeds developed by NRIG to develop and experiment with new software and networking architectures. These activities aim to improve the Internet and ensure next-generation networks can handle large amounts of data securely.

The Global Environment for Network Innovations (GENI) virtual laboratory project, supported by the National Science Foundation (NSF), was one of NRIG’s first forays into federated research infrastructure. The GENI testbed allows researchers to develop and test networks and distributed applications at scale on a connected system that is separate from the Internet. Research published in more than 370 scientific papers has made use of this virtual laboratory.

NRIG’s director Ilya Baldin is the principal investigator for the portion of GENI known as ExoGENI, which is a distributed edge cloud system testbed. In collaboration with researchers led by Jeff Chase from Duke University, Baldin’s team developed the hardware and software necessary to create the cloud system as well as the middleware that controls access to the testbed.

“ExoGENI gave us experience in running a multi-organizational project involving large distributed systems,” said Baldin. “We had to figure out how to structure software development and how to deal with users for a completely new type of system. This experience and the collaborations we formed have proved critical to the success of many other projects.”

For instance, these experiences helped position NRIG to contribute to the NSF-funded cloud network platform known as Chameleon Cloud. This testbed provides tools for computer scientists to conceptualize, assemble, and try new cloud computing approaches. NRIG’s Paul Ruth is co-principal investigator of Chameleon Cloud, which launched in 2015 and entered its third phase of funding in 2020.

Scientists have used Chameleon Cloud to study power management, operating systems, virtualization, high performance computing, distributed computing, networking, security, machine learning, and more. In the third phase of the project, the RENCI team will develop new options for software-defined networking that will allow Chameleon to be compatible with the new NSF-funded FABRIC testbed.

Reimagining the Internet

FABRIC is a next-generation distributed system that combines a cloud system with high-speed optical links to give scientists a place to study new Internet architectures at scale. It will connect specialized testbeds and high-performance computing facilities around the world to create a rich fabric that can be used for a wide variety of experimental activities.

“If computer scientists were to start over and design the Internet from scratch today, it would likely be done in a very different way,” said Baldin, who is part of the leadership team for the FABRIC project. “Due to the huge cost reduction in computing memory and storage, it now seems feasible to add intelligence to the core of the network, rather than just processing data at the end hosts, as is done now.”

FABRIC is being designed to let computer scientists study completely new approaches to storing and processing data on the fly so that they can figure out what might be viable. Although the project is two years into a planned four-year construction, parts of the testbed are already operational, and teams are actively building hardware and software to enable experimenters to use the system.

In October 2020, the NSF funded work to expand FABRIC beyond the U.S. Placing FABRIC nodes overseas will allow experiments to move large amounts of data across long distances. These additional sites will be at the University of Tokyo; CERN, the European Organization for Nuclear Research in Geneva, Switzerland; the University of Bristol in the UK; and the University of Amsterdam.

Making networks smart

One of the latest trends in network design is the use of data-oriented approaches including artificial intelligence and machine learning (AI/ML) to make networks more intelligent. For example, the multi-institutional Poseidon project, funded by the Department of Energy, will leverage testbeds like FABRIC and Chameleon to provide a modeling environment that uses AI/ML to predict the performance of scientific applications on distributed infrastructures.

NRIG’s Anirban Mandal will lead the part of the Poseidon project focused on performance guidance for optimizing workflows. RENCI will also be developing ways to use AI/ML to detect and classify workflow anomalies and help train and validate ML models on the testbeds.

NRIG is also helping to apply AI/ML methods to upgrade AtlanticWave-SDX, a distributed experimental software-defined exchange (SDX), which uses cutting-edge network technology to facilitate data exchange among research and education networks in the U.S. and abroad. AtlanticWave-SDX is critical for research utilizing the Vera C. Rubin Observatory in Chile, which produces 20 terabytes of data each night that must be quickly, securely, and reliably transmitted to the U.S.

NRIG’s Yufeng Xin is leading a team that will help extend the software to create new network monitoring and analysis capabilities that integrate the latest ML technologies. “This monitoring will eventually be used to create a network that can automatically respond to problems,” said Xin. “Detecting and fixing network problems is critical when transferring extremely large amounts of data over long distances.”

Strengthening cyberinfrastructure

CI Compass, one of NRIG’s newest projects, aims to improve the cyberinfrastructure used by NSF Major Facilities, which generate large amounts of data for research in astronomy, physics, environmental science, and other key domains. “Advanced data acquisition, storage, management, integration, mining, visualization, and computational processing services are critical for fulfilling the science missions for the NSF Major Facilities,” said Mandal, who is a co-principal investigator for the project. “We’ll be offering our expertise in computer science and network infrastructure to help enhance their cyberinfrastructure.”

The CI Compass team will provide expertise to help enhance and evolve the Major Facilities cyberinfrastructure, capture and disseminate cyberinfrastructure knowledge and best practices, and enable knowledge sharing among Major Facilities and the broader cyberinfrastructure community.

By delivering on prominent projects involving computer science teams across the U.S. and even around the world, NRIG has built a set of partners who now often approach NRIG to work with them on a variety of cutting-edge projects. The group continues to look for new ways to help computer scientists create a better Internet and to enhance scientific productivity by solving critical cyberinfrastructure problems.