CC* Networking Infrastructure: CICNet - The One-Rutgers Next Generation Data Driven Research Network

CICNet, the One-Rutgers Next Generation Data Driven Research Network, supports the need of an increasingly diverse research community to access distributed data, cloud environments, advanced computing resources and other research instruments, including Sequencers, MRIs, Sensor Arrays, Electron Microscopes, and Radio Telescopes. The overarching goal of this project is to improve the productivity of the research community by removing bottlenecks associated with the movement of data not only between campuses, but with the national cyberinfrastructure ecosystem, including XSEDE, Open Science Grid, Pacific Research Platform, CloudLab, and GENI. With CICNet, Rutgers attempts to create a transformative research environment where central IT and the research community are partners and collaborators.

CICNet evolves under this project to a 40Gbps research and education campus network across Rutgers, with a 100Gbps ScienceDMZ and 100Gbps connectivity to Internet2. CICNet is a research network that is also available as a research project. The partnership between central IT with the research community, including GENI/OpenFlow/SDN researchers, is designed as a model for integrating new network technologies into an existing framework, creating a path for future use both at Rutgers and beyond. The integration of OpenFlow with high performance computing, distributed across multiple campuses (Camden, Newark, and New Brunswick/Piscataway) is an innovative extension that Rutgers does not have in place today. Outreach and training led by the IT staff deploying CICNet and the Rutgers Wireless Research Group, WINLAB, extends the current relationship between both IT and the research and education communities. The completed network upgrade is designed to support significant new scientific research and education opportunities for multiple departments, colleges, and research groups across all Rutgers campuses that require access to remote instruments and/or transfer large datasets.