Current State of the Art for High Performance Wide Area Networks
draft-kcrh-state-of-art-hp-wan-00
Document | Type |
Replaced Internet-Draft
(individual)
Expired & archived
|
|
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Authors | Daniel King , Tim Chown , Chris Rapier , Daniel Huang | ||
Last updated | 2024-08-28 | ||
Replaced by | draft-kcrh-state-of-art-hpwan, draft-kcrh-hpwan-state-of-art | ||
RFC stream | (None) | ||
Intended RFC status | (None) | ||
Formats | |||
Stream | Stream state | (No stream defined) | |
Consensus boilerplate | Unknown | ||
RFC Editor Note | (None) | ||
IESG | IESG state | Replaced by draft-kcrh-state-of-art-hpwan, draft-kcrh-hpwan-state-of-art | |
Telechat date | (None) | ||
Responsible AD | (None) | ||
Send notices to | (None) |
This Internet-Draft is no longer active. A copy of the expired Internet-Draft is available in these formats:
Abstract
High Performance Wide Area Networks (HP-WANs) represent a critical infrastructure for the modern global research and education community, facilitating collaboration across national and international boundaries. These networks, such as Janet, ESnet, GÉANT, Internet2, CANARIE, and others, are designed to support the general needs of the research and education users they serve but also the the transmission of vast amounts of data generated by scientific research, high-performance computing, distributed AI-training and large-scale simulations. This document provides an overview of the terminology and techniques used for existing HP-WANS. It also explores the technological advancements, operational tools, and future directions for HP-WANs, emphasising their role in enabling cutting-edge scientific research, big data analysis, AI training and massive industrial data analysis.
Authors
Daniel King
Tim Chown
Chris Rapier
Daniel Huang
(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)