Subject: I-D Action: draft-kim-nmrg-rl-04.txt

From: [email-masked]
Date: Mon, 11 Mar 2019 02:33:30 -0700

A New Internet-Draft is available from the on-line Internet-Drafts directories.

        Title           : Intelligent Reinforcement-learning-based Network Management
        Authors         : Min-Suk Kim
                          Youn-Hee Han
                          Yong-Geun Hong
	Filename        : draft-kim-nmrg-rl-04.txt
	Pages           : 12
	Date            : 2019-03-11

Abstract:
   This document presents intelligent network management scenarios based
   on reinforcement-learning approaches.  Nowadays, a heterogeneous
   network should usually provide real-time connectivity, the type of
   network management with the quality of real-time data, and
   transmission services generated by the operating system for an
   application service.  With that reason intelligent management system
   is needed to support real-time connection and protection through
   efficient management of interfering network traffic for high-quality
   network data transmission in the both cloud and IoE network systems.
   Reinforcement-learning is one of the machine learning algorithms that
   can intelligently and autonomously provide to management systems over
   a communication network.  Reinforcement-learning has developed and
   expanded with deep learning technique based on model-driven or data-
   driven technical approaches so that these trendy techniques have been
   widely to intelligently attempt an adaptive networking models with
   effective strategies in environmental disturbances over variety of
   networking areas.

The IETF datatracker status page for this draft is:
https://datatracker.ietf.org/doc/draft-kim-nmrg-rl/

There are also htmlized versions available at:
https://tools.ietf.org/html/draft-kim-nmrg-rl-04
https://datatracker.ietf.org/doc/html/draft-kim-nmrg-rl-04

A diff from the previous version is available at:
https://www.ietf.org/rfcdiff?url2=draft-kim-nmrg-rl-04

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