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SDN for End-to-End Networked Science at the Exascale (SENSE)

Authors :
Monga, Inder
Guok, Chin
MacAuley, John
Sim, Alex
Newman, Harvey
Balcas, Justas
DeMar, Phil
Winkler, Linda
Lehman, Tom
Yang, Xi
Monga, Inder
Guok, Chin
MacAuley, John
Sim, Alex
Newman, Harvey
Balcas, Justas
DeMar, Phil
Winkler, Linda
Lehman, Tom
Yang, Xi
Publication Year :
2018

Abstract

The Software-defined network for End-to-end Networked Science at Exascale (SENSE) research project is building smart network services to accelerate scientific discovery in the era of `big data' driven by Exascale, cloud computing, machine learning and AI. The project's architecture, models, and demonstrated prototype define the mechanisms needed to dynamically build end-to-end virtual guaranteed networks across administrative domains, with no manual intervention. In addition, a highly intuitive `intent' based interface, as defined by the project, allows applications to express their high-level service requirements, and an intelligent, scalable model-based software orchestrator converts that intent into appropriate network services, configured across multiple types of devices. The significance of these capabilities is the ability for science applications to manage the network as a first-class schedulable resource akin to instruments, compute, and storage, to enable well defined and highly tuned complex workflows that require close coupling of resources spread across a vast geographic footprint such as those used in science domains like high-energy physics and basic energy sciences.

Details

Database :
OAIster
Notes :
SDN for End-to-End Networked Science at the Exascale (SENSE)
Publication Type :
Electronic Resource
Accession number :
edsoai.on1106559462
Document Type :
Electronic Resource