English

Software-Defined Network for End-to-end Networked Science at the Exascale

Networking and Internet Architecture 2020-04-14 v1

Abstract

Domain science applications and workflow processes are currently forced to view the network as an opaque infrastructure into which they inject data and hope that it emerges at the destination with an acceptable Quality of Experience. There is little ability for applications to interact with the network to exchange information, negotiate performance parameters, discover expected performance metrics, or receive status/troubleshooting information in real time. The work presented here is motivated by a vision for a new smart network and smart application ecosystem that will provide a more deterministic and interactive environment for domain science workflows. The Software-Defined Network for End-to-end Networked Science at Exascale (SENSE) system includes a model-based architecture, implementation, and deployment which enables automated end-to-end network service instantiation across administrative domains. An intent based interface allows applications to express their high-level service requirements, an intelligent orchestrator and resource control systems allow for custom tailoring of scalability and real-time responsiveness based on individual application and infrastructure operator requirements. This allows the science applications to manage the network as a first-class schedulable resource as is the current practice for instruments, compute, and storage systems. Deployment and experiments on production networks and testbeds have validated SENSE functions and performance. Emulation based testing verified the scalability needed to support research and education infrastructures. Key contributions of this work include an architecture definition, reference implementation, and deployment. This provides the basis for further innovation of smart network services to accelerate scientific discovery in the era of big data, cloud computing, machine learning and artificial intelligence.

Keywords

Cite

@article{arxiv.2004.05953,
  title  = {Software-Defined Network for End-to-end Networked Science at the Exascale},
  author = {Inder Monga and Chin Guok and John MacAuley and Alex Sim and Harvey Newman and Justas Balcas and Phil DeMar and Linda Winkler and Tom Lehman and Xi Yang},
  journal= {arXiv preprint arXiv:2004.05953},
  year   = {2020}
}

Comments

To appear in the journal of Future Generation Computer Systems

R2 v1 2026-06-23T14:49:23.581Z