Multi-cluster Edge System Architecture and Network Function Requirements
draft-dwon-t2trg-multiedge-arch-02
| Document | Type |
Expired Internet-Draft
(individual)
Expired & archived
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|---|---|---|---|
| Authors | Dae Won Kim , Joo-Sang Youn | ||
| Last updated | 2023-01-26 (Latest revision 2022-07-25) | ||
| RFC stream | (None) | ||
| Intended RFC status | (None) | ||
| Formats | |||
| Stream | Stream state | (No stream defined) | |
| Consensus boilerplate | Unknown | ||
| RFC Editor Note | (None) | ||
| IESG | IESG state | Expired | |
| 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This Internet-Draft is no longer active.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
Artificial intelligence based IoT applications demand more massive computing resource through networks for the process of AI tasks. To support these applications, some new technologies based an edge computing and fog computing are emerging. Especially, the computation-intensive and latency-sensitive IoT applications such as augmented reality, virtual reality and AI based inference application is deployed with an edge computing and fog computing which are connected with cloud computing. Recently, cluster-based edge system is deployed to extend computation capacity of an edge server. The cluster-based edge system has the advantage that can enhace the resource scalability and availability in edge computing and fog computing. In this draft, we present cluster-based edge system architecture and multi-cluster edge network topology that consists of multi-cluster edge system and core cloud. Also, we define the network functions and network node to configurate and operate multi- cluster edge network collaboratively.
Authors
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