High speed scientific data transfers using software defined networking

Abstract: The massive data volumes acquired, simulated, processed and analyzed by globally distributed scientific collaborations continue to grow exponentially. One leading example is the LHC program, now at the start of its second three year data taking cycle, searching for new particles and interactions in a previously inaccessible range of energies, which has experienced a 70% growth in peak data transfer rates over the last 12 months alone. Other major science programs such as LSST and SKA, and other disciplines ranging from earth observation to genomics, are expected to have similar or great needs than the LHC program within the next decade. The development of new methods for fast, efficient and reliable data transfers over national and global distances, and a new generation of intelligent, software-driven networks capable of supporting multiple science programs with diverse needs for high volume and/or real-time data delivery, are essential if these programs are to continue to progress, and meet their goals. In this paper we describe activities of the Caltech High Energy Physics team and collaborators, related to the use Software Defined Networking to help achieve fast and efficient data distribution and access. Results from Supercomputing 2014 are presented together with our work on the Advanced Network Services for the Experiments project, and a new project developing a Next Generation Integrated SDN Architecture, as well as our plans for Supercomputing 2015.

Recommended citation: H Newman et al. (2015). "High speed scientific data transfers using software defined networking" INDIS '15: Proceedings of the Second Workshop on Innovating the Network for Data-Intensive Science DOI 10.1145/2830318 ISBN 9781450340021 Association for Computing Machinery, New York, NY, United States. http://twh.github.io/files/INDIS2015.pdf