INTRODUCTION TO SELF-ORGANIZING MANAGEMENT...

INTRODUCTION TO SELF-ORGANIZING MANAGEMENT & CONTROL PLANE, ETSI NGP ISG

Sheng JIANG (Principal Engineer, Huawei) on behalf of ETSI NGP ISG

October 19th , 2016, SON Conference, London © ETSI 2014. All rights reserved

Content

Introduction of ETSI NGP

Motivation & Vision for Self-Organizing Network

Protocol support for Self-Organizing Network

Machine Learning for Autonomic Decision

Summary

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ETSI NGP ISP

The TCP/IP protocol suite has enabled the whole Internet since its invention during the 1970’s.

However, since the very beginning, TCP/IP is not perfect. It even stay this way, even after IPv6 replaced and many patches of standardization have been added into the TCP/IP protocol families.

ETSI NGP (Next Generation Protocol) ISG (Industry Specification Group) takes the opportunity along with 5G innovation to enhance the core of Internet further

White paper and WI1 (Scenarios specification) has been published since the creation of NGP in Jan. 2016

Ongoing WI includes: Self-organizing Control & Management Planes; Packet Routing Technologies; Evolved Architecture for mobility using Identity Oriented Networks; and requirements

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Summary

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© ETSI 2014. All rights reserved October 19th , 2016, SON Conference, London

Network Needs Self-Organizing

History of civilization is kind of the progressive history of productive forces, which are represented in modern times as: • Informatization, Networking, Automation, and Intelligence

Seeking of automation is the fountainhead of mankind’s progress

Current situation: Network is becoming complicated • With the increasing of new features and functionalities, network

devices is becoming more complicated; Network control is becoming more multidimensional; New services continuing emerges; diversified network management requirements are growing, beyond the routing reachability

• Control objectives in the network management have complicated relationships, which have not yet been considered

• Network scale increases fast; Number of network devices increases fast; The cooperation and interference among devices are complicated, and out of control

Network configuration relies on the decision and implement of network administrator • Network is changing all the time, and thus the administrator needs to change the

configurations frequently and timely. However, it usually takes a long time to make the change, and/or position the failure

• It is reported that most network problems (above 95%) are caused by human’s misconfiguration

• The administrator is both the key and the bottleneck, even the source of problem

© ETSI 2014. All rights reserved 5 October 19th , 2016, SON Conference, London

http://exceljockey.com/wp-content/uploads/2013/03/complexity_network.jpg

http://exceljockey.com/wp-content/uploads/2013/03/complexity_network.jpg

Evolution of Network

IP Network Distributed Intelligence Autonomic routing

(east and west directions)

Routing

Protocol

Way of evolvement:

•To use more

configuration from

north to south

•Manual intervention of

the network

Network

scale

increases

Complexit

y

increases

Distributed

configurations are short

of cooperation

Way of evolvement:

•Continuing increase the manual intervention

•Rely on the intelligence of the administrator

SDN Centralized Control Policies are provisioned from

north to south

Efficiently deploy

micro innovation

Centralization does not means

more intelligence; it only stands

for the aggregation of

information

Way of evolvement:

•Increase intelligence in multiple

dimensions

•Apply high-level abstract

commands

Distributed Intelligence

nowadays mainly focuses on

forwarding and packet

reachability aspects

Final Target •Reduce the complexity of

network management

•Fulfill the diversified

requirements of users and

services

More sensing and

communication from the east

or west directions

Challenge: Scalability

Network scale is large, and the

complexity will increase

beyond the handling capability

of human

Challenge:

Complexity of policy model

Now

Not

Conflicted

DHCP and ND are also moving towards this

direction, but they are only deployed in the edge

network where the end devices communicate

with the network directly

Self-Organizing

Network self-configuration, self-

management, self-healing,

management based on abstract

intent


Self-Organizing -Reducing the management complexity

Under the requirement of managing network and traffic in a more detailed way, the granularity for network

management becomes more precise. The management model nowadays could not manage future network

anymore (including SDN). Crisis point comes nearer and nearer

A more flexible, extensible and self-management system is urgently needed

A completely automatic/self-organizing solution for network could simplify human management, avoid

human errors, and reduce the cost of network maintenance

© ETSI 2014. All rights reserved 7

October 19th , 2016, SON Conference, London

Vision of Self-Organizing Network

Highly automate network operating; network controls itself; configuration, troubleshooting, and decision making that used to be done by human become autonomic

• Maybe some decisions are made inside a device, while some decisions are made by the whole network through the cooperating of the devices

Minimize human intervention in hardware planning and deployment, service designing and activation; the administrator communicates with the network using a highly abstract operate mode

Self-* functions: self-configuration, self-optimization, self- healing, self-protection, self- every control & management events in networks if possible

Foreseeability, predictive analysis, pre-prepared solution


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Summary

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Needs for Protocol Support

Build up individual autonomic decision processes that could properly

combine to respond to every type of network event

Negotiation among network devices are needed for autonomic decision

Modified from https://tnc2012.terena.org/core/presentation/47

• Configuration• Monitoring• Reporting

• Routing

• Abstract intervene• Abstract Reporting

• Routing• Device Discovery & Configuration• Status Measurement & Notification• Resource Negotiation & Coordination

Human operators

Traditional Future

IPv6 IPv6


• Universal autonomic-oriented signaling protocol platform, which supports generic discovery & negotiation &

synchronization functionalities, independently from any specific objectives

• The intelligent devices would be able to decide the best behaviors by themselves with the knowledge supplying from

other node and network-wide knowledge base

Protocol-oriented Autonomic Network Architecture

Self Knowledge

Status & Measurement Configurations

Network

Knowledge

Autonomic

Control Plane

Generic

Discovery &

Negotiation

Protocol

Traditional

NMS

Autonomic Service Agents

Self Initial

Configuring

More Autonomic

Service Agents

Performance

Management

Routing

Management

Failure detect

& recovery

Secure

Bootstrap

Internal Coordination

Auto Service

Layout Agent

Node-local

Knowledge Base

Network-wide

coordination

Interactive

Service Order Abstract

Report

Management

Intervention

Network-wide Knowledge Base

Naming

Management


IETF ANIMA Working Group

Autonomic network in ANIMA is defined as:

• Autonomic networking refers to the self-managing characteristics (configuration,

protection, healing, and optimization) of distributed network elements, adapting to

unpredictable changes while hiding intrinsic complexity from operators and users

• Autonomic Networking, which often involves closed-loop control, is applicable to

the complete network (functions) lifecycle (e.g. installation, commissioning,

operating, etc)

• An autonomic function that works in a distributed way across various network

elements is a candidate for protocol design (mode suggested, but not mandatory)

Co-existence with traditional modes

• Autonomic functions should allow central guidance and reporting, and

• Co-existence with non-autonomic methods of management

General objective:

• To enable the progressive introduction of autonomic functions into operational

networks, as well as reusable autonomic network infrastructure, in order to reduce

the OpEx

• Focusing on professionally-managed networks


Infrastructure Components for AN

A common way to identify nodes

A common security model

A discovery mechanism

A negotiation mechanism to enable closed-loop interaction

A secure and logically separated communications channel

A consistent autonomic management model

Operational intervention:

Intent: An abstract, high level policy

Coordination Agent/Function to avoiding conflictions

More components might be needed for AN infrastructure

© ETSI 2014. All rights reserved 13


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Summary

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Machine Learning - Mechanism for Self decision

Machine Learning can be used to extract rules used in network management

and classify the various statuses inside and outside the system (obtained from

measuring and monitoring)

• If the detected event or situation has been considered in designing time, the network is normally able

to deal with it according to the solution defined by the designer. This is traditional system design

• If not, the case is classified as “uncertainty”. Artificial intelligence is needed for this case

Artificial intelligence can make decision, and make the system have the

capability of solving problem all by itself

• Artificial intelligence is also realized by algorithms, but these algorithms have a

certain degree of generic characteristic, thus developing a specific logic for every new

situation is no more needed

Some technologies in artificial intelligence can also be used in data analysis;

on the other side, traditional data analysis technologies are also used in

artificial intelligence

Machine learning is the only way to percept unknown without human

intervention; however, it is not suitable for real-time decision. Real-time

decision needs processed rules and real-time small data © ETSI 2014. All rights reserved 15


Auto-Configuration

Machine Learning methodology and algorithms is used to construct decision knowledge

and intelligence in order to achieve autonomic configurations

Make the network planning as a Constraint Input; make the comparable data collection of

historic configuration (including data from other nodes in the network or even other

networks) as a Referencing Input

Traditional Approach

Network Planning（HLD）

|

Config/Para Planning（LLD）

|

Generating config templates

|

Generating config files

for each device

|

Binding config files to each devices in NMS

|

Device getting online, downloading the matching

config files

DM/ML Approach

Network Planning （HLD）

|

Protocol/Function

Level Planning

(no parameters planning)

|

Transferring Planning to Data

|

Device getting online, parameters are

autoconfigured

Manual Semi-automatic (Manual+tools）

Automatic

Offline Analysis (Based on historical data)

Online Prediction

DM System


The Proposed NMLRG in IRTF

Network Machine Learning Research Group (NMLRG)

It provides a forum for researchers to explore the potential of machine

learning technologies for networks. In particular, the NMLRG will work on

potential approaches that apply machine learning technologies in network

control, network management, and supplying network data for upper-layer

applications

The NMLRG is expected to identify and document requirements, to survey

possible approaches, to provide specifications for proposed solutions, and

to prove concepts with prototype implementations that can be tested in real-

world environments

The works/presentations may visibility to IETF participants. Some

identified hard problems or standardization works may be output to IETF in

the future, also maybe directly to the industry deployment


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Summary

Self-organizing mechanisms allow network to be managed by themselves. It would reduce complexity of network management and the OPEX of network operators

Self-organizing networking requires support for new network protocols, new algorithms/mechanisms for autonomic decision

ETSI NGP ISG works on the next generation protocol to support future self-organizing (autonomic) networks in a manner of harmonizing with other standard organization, IETF, IRTF, 3GPP, etc.

19 © ETSI 2014. All rights reserved October 19th , 2016, SON Conference, London

The NGP ISG is open to all ETSI members and non-members

For full details of the NGP ISG including

ToR – Members and Participants agreements and how to join, please visit

https://portal.etsi.org/tb.aspx?tbid=844&SubTB=844

Thank you!

Welcome to the NGP ISG

20 October 19th , 2016, SON Conference, London

© ETSI 2014. All rights reserved






http://portal.etsi.org/tb.aspx?tbid=833&SubTB=833

Self-organizing Network Scenarios

Self-

Configuratio

n

Auto Service

Orchestration

Self Fault

Management

Self

Optimization Self Defense

Autonomically

& dynamically

configure all

network

devices

Receiving

service request

in abstract or

nature language,

then auto

deploying

Autonomically

discover the

network fault

and correct soft

errors

Autonomically

optimize the

network

resources or

traffic

engineering

Dynamically

recognize to

new attacks and

adaptively

defense

Learn current

configurations,

then apply to

new network or

network

changes

Learn existing

services config,

resolving

abstract service

request

learn & analysis

from historic

faults and recent

logs & real-time

measurement

Real-time

measure the

reaction of

network from

changing the

configuration

Learn &

analysis the

network attack

behaviors

Autonomically managing network objectives (using real-time mechanism for

autonomic decision)


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