Internet DRAFT - draft-li-rtgwg-network-ai-arch
draft-li-rtgwg-network-ai-arch
Network Working Group Z. Li
Internet-Draft J. Zhang
Intended status: Informational Huawei Technologies
Expires: May 4, 2017 October 31, 2016
An Architecture of Network Artificial Intelligence(NAI)
draft-li-rtgwg-network-ai-arch-00
Abstract
Artificial intelligence is an important technical trend in the
industry. With the development of network, it is necessary to
introduce artificial intelligence technology to achieve self-
adjustment, self- optimization, self-recovery of the network through
collection of huge data of network state and machine learning. This
draft defines the architecture of Network Artificial Intelligence
(NAI), including the key components and the key protocol extension
requirements.
Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described inRFC 2119 [RFC2119]
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
working documents as Internet-Drafts. The list of current Internet-
Drafts is at http://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on May 4, 2017.
Copyright Notice
Copyright (c) 2016 IETF Trust and the persons identified as the
document authors. All rights reserved.
Li & Zhang Expires May 4, 2017 [Page 1]
Internet-Draft An Architecture of NAI October 2016
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents
(http://trustee.ietf.org/license-info) in effect on the date of
publication of this document. Please review these documents
carefully, as they describe your rights and restrictions with respect
to this document. Code Components extracted from this document must
include Simplified BSD License text as described in Section 4.e of
the Trust Legal Provisions and are provided without warranty as
described in the Simplified BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Architecture . . . . . . . . . . . . . . . . . . . . . . . . 3
3.1. Reference Model . . . . . . . . . . . . . . . . . . . . . 3
3.2. Requirement of Protocol Extensions . . . . . . . . . . . 4
4. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 5
5. Security Considerations . . . . . . . . . . . . . . . . . . . 5
6. Normative References . . . . . . . . . . . . . . . . . . . . 5
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 5
1. Introduction
Artificial Intelligence is an important technical trend in the
industry. The two key aspects of Artificial Intelligence are
perception and cognition. Artificial Intelligence has evolved from
an early non-learning expert system to a learning-capable machine
learning era. In recent years, the rapid development of the deep
learning branch based on the neural network and the maturity of the
big data technology and software distributed architecture make the
Artificial Intelligence in many fields (such as transportation,
medical treatment, education, etc.) have been applied. With the
development of network, it is necessary to introduce artificial
intelligence technology to achieve self-adjustment, self-
optimization, self-recovery of the network through collection of huge
data of network state and machine learning. The areas of machine
learning which are easier to be used in the network field may
include: troubleshooting of network problems, network traffic
prediction, traffic optimization adjustment, security defense,
security auditing, etc., to implement network perception and
cognition.
This draft defines the architecture of Network Artificial
Intelligence (NAI), including the key components and the key protocol
extension requirements.
Li & Zhang Expires May 4, 2017 [Page 2]
Internet-Draft An Architecture of NAI October 2016
2. Terminology
AI: Artificial Intelligence
NAI: Network Artificial Intelligence
3. Architecture
3.1. Reference Model
+------------------------------+ +------------------------------+
| Domain 1 | | Domain 2 |
| +------------+ | | +------------+ |
| | Central | | | | Central | |
| | Controller |----------------------| Controller | |
| | | | | | | |
| | | | | | | |
| +------------+ | | +------------+ |
| / \ | | / \ |
| / \ | | / \ |
| / \ | | / \ |
| +--------+ +--------+ | | +--------+ +--------+ |
| | | | | | | | | | | |
| |Network | ...... |Network | | | |Network | ...... |Network | |
| | Device | | Device | | | | Device | | Device | |
| | 1 | | N | | | | 1 | | N | |
| +--------+ +--------+ | | +--------+ +--------+ |
| | | |
+------------------------------+ +------------------------------+
Figure 1: An Architecture of Network Artificial Intelligence(NAI)
The architecture of Network artificial intelligence includes
following key component:
1. Central Controller: Centralized controller is the core component
of Network Artificial Intelligence which can be called as 'Network
Brain'. It man collect huge data of network states, store the data
based on the big data platform, and carry on the machine learning, to
achieve network perception and cognition, including network self-
optimization, self- adjustment, self-recovery, intelligent fault
location and a series of network artificial intelligence goals.
2. Network Device: IP network operation and maintenance are always a
big challenge since the network can only provide limited state
information. The network states includes but are not limited to
topology, traffic engineering, operation and maintenance information,
network failure information and related information to locate the
Li & Zhang Expires May 4, 2017 [Page 3]
Internet-Draft An Architecture of NAI October 2016
network failure.. In order to provide these information, the network
must be able to support more OAM mechanisms to acquire more state
information and report to the controller. Then the controller can
get the complete state information of the network which is the base
of Network Artificial Intelligence(NAI).
3. Southbound Protocol and Models of Controller: As network devices
provide huge network state information, it proposes a number of new
requirements for protocols and models between controllers and network
devices. The traditional southbound protocol such as Netconf and
SNMP can not meet the performance requirements. It is necessary to
introduce some new high-performance protocols to collect network
state data. At the same time, the models of network data should be
completed. Moreover with the introduction of new OAM mechanisms of
network devices, new models of network data should be introduced.
4. Northbound Model of Controller: The goal of the Network
Artificial Intelligence is to reduce the technical requirements on
the network administrators and release them from the heavy network
management, control, maintenance work. The abstract northbound model
of the controller for different network services should be simple and
easy to be understood.
3.2. Requirement of Protocol Extensions
REQ 01: The new southbound protocol of the controller should be
introduced to meet the performance requirements of collecting huge
data of network states.
REQ 02: The models of network elements should be completed to collect
the network states based on the new southbound protocol of the
controller.
REQ 03: New OAM mechanisms should be introduced for the network
devices in order to acquire more types of network state data.
REQ 04: New models of network elements should be introduced as the
new OAM mechanisms are introduced.
REQ 05: The operation models of network elements should be completed
based on the new southbound protocol to carry on the corresponding
network operation as the result of Network Artificial Intelligence.
REQ 06: The abstract network-based service models should be provided
by the controller as the northbound models to satisfy the
requirements of different services.
Li & Zhang Expires May 4, 2017 [Page 4]
Internet-Draft An Architecture of NAI October 2016
4. IANA Considerations
This document makes no request of IANA.
5. Security Considerations
TBD.
6. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<http://www.rfc-editor.org/info/rfc2119>.
Authors' Addresses
Zhenbin Li
Huawei Technologies
Huawei Bld., No.156 Beiqing Rd.
Beijing 100095
China
Email: lizhenbin@huawei.com
Jinhui Zhang
Huawei Technologies
Huawei Bld., No.156 Beiqing Rd.
Beijing 100095
China
Email: jason.zhangjinhui@huawei.com
Li & Zhang Expires May 4, 2017 [Page 5]
