The Innovating the Network for Data-Intensive Science workshop brings together network engineers and researchers to share challenges and potential solutions in the information systems and networking communities.

With its inaugural appearance at SC14 in New Orleans, INDIS has become an academic forum for experts, researchers, and engineers in research and education (R&E) networking.

The workshop encourages research papers that address one or more of the networking needs; and developments that are essential in the information systems infrastructure for the scientific discovery process.

This workshop also serves as a platform for participants in SCinet, the high-speed network built for the SC conference, to present experimental papers on their latest designs and solutions. SCinet, as a state-of-the-art network, connects many demonstrators of big science data processing infrastructures at the highest line speeds, deploys the newest technologies available, and demonstrates novel functionality.

We invite papers that propose new and novel techniques that increase the capacity and functionality of scientific computing and wide-area networks.

Topics of interest include but are not limited to:

  • High-speed network protocols
  • Network architectures
  • Securing high-speed networks
  • High performance data transfer applications and techniques
  • Science DMZs and other campus network constructs
  • Software-defined networking and programmable networks
  • Virtual Network Functions
  • Optical networking
  • Network Orchestration, Topology and Analytics
  • Requirements and issues for network quality of service (QoS)
  • Network management: diagnostics, troubleshooting, fault management, performance monitoring, configuration management
  • Multi-domain networking

Workshop Organizers:

  • Paola Grosso, Associate professor in the System and Network Engineering (SNE) group at the University of Amsterdam, The Netherlands.
  • Ilya Baldin, Director, Networking Research and Infrastructure, RENCI/UNC Chapel Hill
  • Mary Hester, Community Manager at SURFnet, The Netherlands
  • Michelle Zhu, Associate Professor, Computer Science Department, Montclair State University


Programme Committee

  • Anirban Mandal, Renaissance Computing Institute, USA
  • Anna Giannakou,Lawrence Berkeley National Laboratory, USA
  • Brad Cowie, University of Waikato, NZ
  • Brian L. Tierney, Lawrence Berkeley National Laboratory, USA
  • Caroline Carver, Weilhamer Indiana University, USA
  • Cees de Laat, University of Amsterdam, NL
  • Chase Q. Wu, New Jersey Institute of Technology, USA
  • Chris Tracy, Energy Sciences Network, USA
  • Dawei Li, Montclair State University, USA
  • Eric Pouyoul, Energy Sciences Network, USA
  • Fei Yeh, Northwestern University, International Center for Advanced Internet Research (iCAIR), USA
  • Gi Vania, University of Texas, Dallas, USA
  • Gonzalo P. Rodrigo, Lawrence Berkeley National Laboratory, USA
  • Guillaume Aupy, French Institute for Research in Computer Science and Automation (INRIA), FR
  • Iara Machado, RNP, Brazil
  • Ilya Baldin, Renaissance Computing Institute, USA
  • Jim Stewart, Utah Education Network, USA
  • Jim Hao Chen, Northwestern University, USA
  • Josh Bailey, Google LLC, NZ
  • Judith C. Hill, Oak Ridge National Laboratory, USA
  • Leandro Ciuffo, RNP, Brazil
  • Linda Winkler, Argonne National Laboratory, USA
  • Marc Lyonnais, Ciena Corporation
  • Mary Hester, SURFnet, NL
  • Michael Stanton, RNP, Brazil
  • Michelle Zhu, Montclair State University, USA
  • Nick Buraglio, ESnet, USA
  • Paola Grosso, University of Amsterdam, NL
  • Paul Ruth, Renaissance Computing Institute, USA
  • Raj Kettimuthu, Argonne National Laboratory, USA
  • Richard R. Brooks, Clemson University, USA
  • Richard Hughes-Jones, GÉANT, Cambridge, UK
  • Rod Wilson, Ciena Corporation, Canada
  • Se-Young Yu, International Center for Advanced Internet Research (iCAIR), USA