ETSI TR 103 626 V1.1.1 (2020-02)

TECHNICAL REPORT
Autonomic network engineering
for the self-managing Future Internet (AFI);
An Instantiation and Implementation of the
Generic Autonomic Network Architecture (GANA)
Model onto Heterogeneous Wireless Access Technologies
using Cognitive Algorithms
2 ETSI TR 103 626 V1.1.1 (2020-02)

Reference
DTR/INT-001-AFI-0027
Keywords
autonomic networking, cognition, cognitive,
control, radio, self-management

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3 ETSI TR 103 626 V1.1.1 (2020-02)
Contents
Intellectual Property Rights . 5
Foreword . 5
Modal verbs terminology . 5
1 Scope . 6
2 References . 6
2.1 Normative references . 6
2.2 Informative references . 6
3 Definition of terms, symbols and abbreviations . 9
3.1 Terms . 9
3.2 Symbols . 10
3.3 Abbreviations . 10
4 Principles for Autonomic Networking and Enablers . 13
4.1 Overview on Autonomics Principles and Enablers, and introduction to the emerging concept of
"Network compartmentation" . 13
4.2 Function atomization . 14
4.3 Function composition . 14
4.4 Closed control loop (s) . 14
4.5 Context recognition and adaptation . 15
4.6 Introduction to the GANA Reference Model for Autonomic Networking, Cognitive Networking and
Self-Management . 15
4.6.1 Overview . 15
4.6.2 Examples of Autonomic Management & Control (AMC) domains . 17
5 WiSHFUL Architecture . 18
5.1 Overview . 18
5.1.1 General overview of the WiSHFUL Concepts . 18
5.1.2 How Control Programs in the WiSHFUL Architecture are the means to realize (implement) specific
GANA Decision Elements (DEs) . 20
5.2 WiSHFUL platforms and abstractions . 20
5.3 Adaptation Modules . 22
5.4 Unified Program Interface . 22
5.4.1 Overview on WiSHFUL Unified Program Interfaces (UPIs) . 22
5.4.2 UPI_M . 23
5.4.3 UPI_N . 23
5.4.4 UPI_R . 23
5.5 WiSHFUL Control Framework . 24
5.5.1 Control Concepts and programmability enablers implemented in the environments that were
considered by WiSHFUL . 24
5.5.2 Interaction models . 25
5.5.3 Immediate and delayed commands . 25
5.5.4 Local and remote execution . 25
5.5.5 Synchronization . 25
5.5.6 Packet monitoring and manipulation . 26
5.5.7 Node handling . 26
5.5.8 Extensibility of UPI functions . 26
5.6 Hierarchical Control Model . 26
5.7 Monitor and configuration engines and services . 28
5.8 Execution engines, radio and control programs . 28
5.8.1 Overview . 28
5.8.2 WMP . 28
5.8.3 TAISC . 29
5.9 Intelligence framework (data collection, intelligence composition, action) . 29
6 Impact of Virtualization and Hardware Acceleration Techniques, and Radio Access Network
Slicing (RAN Slices), to WiSHFUL Concepts and Principles . 30
ETSI
4 ETSI TR 103 626 V1.1.1 (2020-02)
7 Instantiation of GANA Functional Blocks by Mapping WiSHFUL architecture components to
GANA Concepts and Architectural Principles . 33
7.1 General Mapping of WiSHFUL Architectural Concepts and Principles to GANA Concepts and
Principles . 33
7.2 Autonomic networks and General GANA integration with SDN, NFV, Big Data Analytics Applications,
OSS/BSS Systems, Orchestrators, and Other Management and Control Systems . 35
7.3 WiSHFUL Node-level programmability and Mapping to GANA Node-Level and Lower Levels

Autonomics . 37
7.4 WiSHFUL Network-level programmability and the Mapping to GANA Network Level (Knowledge
Plane (KP) Level) Autonomics . 39
7.5 Parameter and Functionality Mappings for DE-to-ME Associations that enable DE implementers to
implement DEs . 42
7.6 Instantiation of the GANA Knowledge Plane (KP) in the WiSHFUL Intelligence Framework . 43
7.7 Instantiation (Implementation) of GANA Reference Points in the WiSHFUL Architecture
Implementation . 44
8 Additional Resourceful Information that should be considered by Implementers of GANA DEs . 52
9 Conclusions and Further Work . 53
History . 54

ETSI
5 ETSI TR 103 626 V1.1.1 (2020-02)
Intellectual Property Rights
Essential patents
IPRs essential or potentially essential to normative deliverables may have been declared to ETSI. The information
pertaining to these essential IPRs, if any, is publicly available for ETSI members and non-members, and can be found
in ETSI SR 000 314: "Intellectual Property Rights (IPRs); Essential, or potentially Essential, IPRs notified to ETSI in
respect of ETSI standards", which is available from the ETSI Secretariat. Latest updates are available on the ETSI Web
server (https://ipr.etsi.org/).
Pursuant to the ETSI IPR Policy, no investigation, including IPR searches, has been carried out by ETSI. No guarantee
can be given as to the existence of other IPRs not referenced in ETSI SR 000 314 (or the updates on the ETSI Web
server) which are, or may be, or may become, essential to the present document.
Trademarks
The present document may include trademarks and/or tradenames which are asserted and/or registered by their owners.
ETSI claims no ownership of these except for any which are indicated as being the property of ETSI, and conveys no
right to use or reproduce any trademark and/or tradename. Mention of those trademarks in the present document does
not constitute an endorsement by ETSI of products, services or organizations associated with those trademarks.
Foreword
This Technical Report (TR) has been produced by ETSI Technical Committee Core Network and Interoperability
Testing (INT).
Modal verbs terminology
In the present document "should", "should not", "may", "need not", "will", "will not", "can" and "cannot" are to be
interpreted as described in clause 3.2 of the ETSI Drafting Rules (Verbal forms for the expression of provisions).
"must" and "must not" are NOT allowed in ETSI deliverables except when used in direct citation.

ETSI
6 ETSI TR 103 626 V1.1.1 (2020-02)
1 Scope
The present document provides a mapping of architectural components for autonomic network management & control
developed/implemented in the European Commission (EC) funded WiSHFUL Project to the ETSI TC INT AFI Generic
Autonomic Networking Architecture (GANA) model - an architectural reference model for autonomic networking,
cognitive networking and self-management. The mapping pertains to architectural components for autonomic decision-
making and associated control-loops in wireless network architectures and their associated management and control
architectures.
The objective is to illustrate how the GANA can be implemented using the components developed in the WiSHFUL
and ORCA Projects. To show the extent to which the WiSHFUL architecture augmented with some virtualization and
hardware acceleration techniques, developed in the ORCA project, implements the GANA model, in order to guide the
industry (implementers of autonomics components for autonomic networks and their associated autonomic management
& control architectures) on how to leverage this work in their efforts on GANA implementations.
The mapping of the components to the GANA model concepts serves to illustrate how to implement the key abstraction
levels for autonomics (self-management functionality) in the GANA model for the targeted wireless networks context,
taking into consideration the work done in ETSI TR 103 495 [i.7].
The other objective is to also illustrate the value of joint autonomic management and control of heterogeneous wireless
access technologies in such a GANA implementation context, with illustration on where Cognitive algorithms for
autonomics (such as Machine Learning and other AI algorithms) can be applied in joint autonomic management &
control of heterogeneous wireless access networks.
The present document answers the question of how to implement the ETSI GANA model using WiSHFUL architecture
and ORCA concepts.
NOTE: Trademarks in the present document that are associated with the environments considered by WiSHFUL
and ORCA projects in their implementation and prototyping of components are only mentioned as
Citation of the environments on which components were implemented by the the two projects. The
purpose of the present document is to illustrate to the industry how such WiSHFUL and ORCA
components can be used to implement the ETSI GANA components in such environments considered by
the projects, while making it clear that other environments not considered by the two projects can also be
considered by the industry in implementing GANA components, as the present document does not serve
to endorse or limit environments in which the GANA components can be implemented.
2 References
2.1 Normative references
Normative references are not applicable in the present document.
2.2 Informative references
References are either specific (identified by date of publication and/or edition number or version number) or
non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the
referenced document (including any amendments) applies.
NOTE: While any hyperlinks included in this clause were valid at the time of publication ETSI cannot guarantee
their long term validity.
The following referenced documents are not necessary for the application of the present document but they assist the
user with regard to a particular subject area.
[i.1] Joao F. Santos, Jonathan van de Belt, Wei Liu, Vincent Kotzsch, Gerhard Fettweis, Ivan Seskar,
Sofie Pollin, Ingrid Moerman, Luiz A. DaSilva and Johann Marquez-Barja: "Orchestrating next-
generation services through end-to-end network slicing", ORCA white paper.
NOTE: Available at https://orca-project.eu/wp-
content/uploads/sites/4/2018/10/orchestrating_e2e_network_slices_Final.pdf.
ETSI
7 ETSI TR 103 626 V1.1.1 (2020-02)
[i.2] ORCA Deliverable 4.3: "Enhanced operational SDR platforms with end-to-end capabilities".
NOTE: Available at https://orca-project.eu/wp-content/uploads/sites/4/2019/02/ORCA_D4.3_final.pdf.
[i.3] WiSHFUL Project Deliverable D3.2: "First operational radio control software platform".
[i.4] WiSHFUL Project Deliverable D3.4: "Second operational radio control software platform".
[i.5] WiSHFUL Project Deliverable D4.2: "First operational network control software platform".
[i.6] WiSHFUL Project Deliverable D4.4: "Second operational network control software platform".
[i.7] ETSI TR 103 495: "Network Technologies (NTECH); Autonomic network engineering for the
self-managing Future Internet (AFI); Autonomicity and Self-Management in Wireless
Ad-hoc/Mesh Networks: Autonomicity-enabled Ad-hoc and Mesh Network Architectures".
[i.8] Tayeb Ben Meriem, Ranganai Chaparadza, Benoît Radier, Said Soulhi, José-Antonio Lozano-
López, Arun Prakash, ETSI White Paper No. 16: "GANA - Generic Autonomic Networking
Architecture - Reference Model for Autonomic Networking, Cognitive Networking and Self-
Management of Networks and Services", First edition, October 2016
ISBN No. 979-10-92620-10-8.
[i.9] ETSI TS 103 195-2 (V1.1.1) (2018-05): "Autonomic network engineering for the self-managing
Future Internet (AFI); Generic Autonomic Network Architecture; Part 2: An Architectural
Reference Model for Autonomic Networking, Cognitive Networking and Self-Management".
[i.10] ETSI TR 103 473 (V1.1.2) (2018-12): "Evolution of management towards Autonomic Future
Internet (AFI); Autonomicity and Self-Management in the Broadband Forum (BBF)
Architectures".
[i.11] ETSI TR 103 404: "Network Technologies (NTECH); Autonomic network engineering for the
self-managing Future Internet (AFI); Autonomicity and Self-Management in the Backhaul and
Core network parts of the 3GPP Architecture".
[i.12] IEEE 802.11™-2016: "IEEE Standard for Information technology--Telecommunications and
information exchange between systems Local and metropolitan area networks--Specific
requirements - Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY)
Specifications".
[i.13] IEEE 802.15.4™: "IEEE Standard for Low-Rate Wireless Networks".
[i.14] White Paper No.2 of the ETSI 5G: "PoC: ONAP Mappings to the ETSI GANA Model; Using
ONAP Components to Implement GANA Knowledge Planes and Advancing ONAP for
Implementing ETSI GANA Standard's Requirements and C-SON: ONAP Architecture".
NOTE Available at https://intwiki.etsi.org/index.php?title=Accepted_PoC_proposals.
[i.15] ETSI GS AFI 002: "Autonomic network engineering for the self-managing Future Internet (AFI);
Generic Autonomic Network Architecture (An architectural Reference Model for Autonomic
Networking, Cognitive Networking and Self-Management)".
[i.16] ETSI INT PoC: "5G Network Slices Creation, Autonomic Management & E2E Orchestration, with
Closed-Loop (Autonomic) Service Assurance for the Slices: IoT (Smart Insurance) Use Case".
NOTE Available at https://intwiki.etsi.org/index.php?title=Accepted_PoC_proposals.
[i.17] Advanced Python Scheduler.
NOTE Available at http://apscheduler.readthedocs.io/en/latest/.
[i.18] ETSI TS 103 194: "Network Technologies (NTECH); Autonomic network engineering for the
self-managing Future Internet (AFI); Scenarios, Use Cases and Requirements for Autonomic/Self-
Managing Future Internet".
ETSI
8 ETSI TR 103 626 V1.1.1 (2020-02)
[i.19] WiSHFUL UPI reference specification for management (M), Network (N), Radio (R) interfaces as
well as network helpers.
NOTE Available at https://wishful-project.github.io/wishful_upis/index.html.
[i.20] Report on Specifications of Integration APIs for the ETSI GANA Knowledge Plane Platform with
Other Types of Management & Control Systems, and with Info/Data/Event Sources in general.
NOTE Available at https://intwiki.etsi.org/index.php?title=Accepted_PoC_proposals.
[i.21] Dunkels A., Gronvall B., Voigt T.: "Contiki a Lightweight and Flexible Operating System for Tiny
th
Networked Sensors". In Proceedings of the 9 Annual IEEE™ International Conference on Local
Computer Networks, Washington, DC, USA, October 2004; pp. 455-462.
[i.22] E. Blossom. Gnu software radio.
NOTE Available at http://gnuradio.org.
[i.23] Ruckebusch P., De Poorter E., Fortuna C., and Moerman I. (2016): "GITAR: Generic extension
for Internet-of-Things ARchitectures enabling dynamic updates of network and application
modules". Ad Hoc Networks, Volume 36, Part 1, January 2016, Pages 127-151.
[i.24] WiSHFUL Project Deliverable D2.1: "High level requirements for testbeds and software
platforms".
[i.25] WiSHFUL Project Deliverable D2.2: "Specification of first showcases".
[i.26] WiSHFUL UPI definition.
NOTE: Available at https://wishful-project.github.io/wishful_upis/wishful_upis.html.
[i.27] ZeroMQ Realtime Exchange Protocol.
NOTE Available at http://rfc.zeromq.org/spec:36.
[i.28] ORCA (Orchestration and Reconfiguration Control Architecture) project website.
NOTE Available at https://www.orca-project.eu.
[i.29] Tarik Kazaz, Wei Liu, Xianjun Jiao, Ingrid Moerman, Francisco Paisana, Clemens Felber, Vincent
Kotzsch, Ivan Seskar, Tom Vermeulen, Sofie Pollin, Martin Danneberg and Roberto Bomfin:
"Orchestration and Reconfiguration Control", EUCNC June 2017. Oulu, Finland.
[i.30] ORCA Deliverable 2.1: "Technical requirements of the ORCA test facility".
NOTE Available at https://orca-project.eu/wp-content/uploads/sites/4/2017/01/ORCA_D2.2_Final_v1.1.pdf.
[i.31] Wei Liu, Joao F. Santos, Jonathan van de Belt, Xianjun Jiao, Ingrid Moerman, Johann Marquez-
Barja, Luiz DaSilva and Sofie Pollin: "Enabling Virtual Radio Functions on Software Defined
Radio for Future Wireless Networks", to appear in Wireless Personal Communications.
[i.32] R. Chaparadza, et al.: "SDN Enablers in the ETSI AFI GANA Reference Model for Autonomic
Management & Control (emerging standard), and Virtualisation Impact". In the proceedings of the
th
5 IEEE™ MENS Workshop at IEEE Globecom 2013, December, Atlanta, Georgia, USA.
[i.33] White Paper No.4 of the ETSI 5G PoC: "ETSI GANA as Multi-Layer Artificial Intelligence (AI)
Framework for Implementing AI Models for Autonomic Management & Control (AMC) of
Networks and Services; and Intent-Based Networking (IBN) via GANA Knowledge Planes".
NOTE Available at https://intwiki.etsi.org/index.php?title=Accepted_PoC_proposals.
[i.34] White Paper No.1: "C-SON Evolution for 5G, Hybrid SON Mappings to the ETSI GANA Model,
and achieving E2E Autonomic (Closed-Loop) Service Assurance for 5G Network Slices by Cross-
Domain Federated GANA Knowledge Planes".
NOTE Available at https://intwiki.etsi.org/images/ETSI_GANA_in_5G_PoC_White_Paper_No_1_v1.28.pdf.
ETSI
9 ETSI TR 103 626 V1.1.1 (2020-02)
[i.35] White Paper No.3: "Programmable Traffic Monitoring Fabrics that enable On-Demand Monitoring
and Feeding of Knowledge into the ETSI GANA Knowledge Plane for Autonomic Service
Assurance of 5G Network Slices; and Orchestrated Service Monitoring in NFV/Clouds".
NOTE Available at https://intwiki.etsi.org/images/ETSI_5G_PoC_White_Paper_No_3_2019_v1.19.pdf.
[i.36] White Paper No.5: "Artificial Intelligence (AI) in Test Systems, Testing AI Models and the ETSI
GANA Model's Cognitive Decision Elements (DEs) via a Generic Test Framework for Testing
ETSI GANA Multi-Layer Autonomics & their AI Algorithms for Closed-Loop Network
Automation".
NOTE Available at https://intwiki.etsi.org/index.php?title=Accepted_PoC_proposals.
[i.37] White Paper No.6: "Generic Framework for Multi-Domain Federated ETSI GANA Knowledge
Planes (KPs) for End-to-End Autonomic (Closed-Loop) Security Management & Control for 5G
Slices, Networks/Services".
NOTE Available at https://intwiki.etsi.org/index.php?title=Accepted_PoC_proposals.
3 Definition of terms, symbols and abbreviations
3.1 Terms
For the purposes of the present document, the following terms apply:
Autonomic Behaviour (AB): process which understands how desired Managed Entity (ME) behaviours are learned,
influenced or changed, and how, in turn, these affect other elements, groups and networks [i.18]
NOTE: In the GANA model, an autonomic behaviour is any behaviour of a DE that is observable on its
interfaces. A GANA DE is also called an Autonomic Function (AF).
autonomic networking: networking paradigm that enables network devices or elements (physical or virtual) and the
overall network architecture and its management and control architecture to exhibit the so-called self-managing
properties, namely:
• Auto-discovery of information and entities
• Self-configuration (auto-configuration), Self-diagnosing, Self-repair (Self-healing)
• Self-optimization, and other self-* properties
NOTE 1: Autonomic Networking can also be interpreted as a discipline involving the design of systems (e.g.
network nodes) that are self-managing at the individual system levels and together as a larger system that
forms a communication network of systems.
NOTE 2: The term "autonomic" comes from the autonomic nervous system (a closed control loop structure), which
controls many organs and muscles in the human body. Usually, humans are unaware of its workings
because it functions in an involuntary, reflexive manner - for example, humans do not notice when their
heart beats faster or their blood vessels change size in response to temperature, posture, food intake,
stressful experiences and other changes to which human are exposed. And their autonomic nervous
system is always working [i.18].
Decision Making Element (DME): functional entity designed and assigned to autonomically manage and control its
assigned Managed Entities (MEs) by dynamically (re)-configuring the MEs and their configurable and controllable
parameters in a closed-control loop fashion
NOTE 1: Decision Making Elements (DMEs) [i.19] referred in short as Decision Elements (DEs) fulfil the role of
Autonomic Manager Elements.
NOTE 2: In GANA a DE is assigned (by design) to very specific MEs that it is designed to autonomically manage
and control (ETSI GS AFI 002 [i.15] provides more details on the notion of ownership of MEs by
specific DEs required in a network element architecture and the overall network architecture).
ETSI
10 ETSI TR 103 626 V1.1.1 (2020-02)
Managed Entities (MEs): physical or logical resource that can be managed by an Autonomic Manager Element (i.e. a
Decision Element) in terms of its orchestration, configuration and re-configuration through parameter settings [i.18]
NOTE: MEs and their associated configurable parameters are assigned to be managed and controlled by a
concrete DE such that an ME parameter is mapped to one DE. MEs can be protocols, whole protocol
stacks, and mechanisms, meaning that they can be fundamental functional and manageable entities at the
bottom of the management hierarchy (at the fundamental resources layer in a network element or node)
such as individual protocols or stacks, OSI layer 7 or TCP/IP application layer applications and other
types of resources or managed mechanisms hosted in a network element (NE) or in the network in
general, whereby an ME exposes a management interface through which it can be managed. MEs can also
be composite MEs such as whole NEs themselves (i.e. MEs that embed sub-MEs).
OpenWRT: According to https://openwrt.org/ OpenWRT is a Linux™ operating system for people who want to install
high-performance, easily-configured, reliable and robust firmware on a home router or embed the Linux-based software
in other equipment.
overlay: logical network that runs on top of another network
EXAMPLE: Peer-to-peer networks are overlay networks on the Internet. They use their own addressing system
for determining how files are distributed and accessed, which provides a layer on top of the
Internet's IP addressing.
self-advertising: capability of a component or system to advertise its self-model, capability description model, or some
information signalling message (such as an IPv6 router advertisement message) to the network in order to enable other
entities to discover it and be able to communicate with it, or to enable other entities to know whatever is being
advertised
self-awareness: capability of a component or system to "know itself" and be aware of its state and its behaviours
NOTE: Knowledge about "self" is described by a "self-model".
self-configuration: capability of a component or system to configure and reconfigure itself under varying and
unpredictable conditions
self-healing: capability of a component or system to detect and recover from problems (manifestations of faults, errors,
failures, and other forms of degradation) and continue to function smoothly
self-monitoring: capability of a component or system to observe its internal state, for example by monitoring quality-
of-service metrics such as reliability, precision, rapidity, or throughput
self-optimization: capability of a component or system to detect suboptimal behaviours and optimize itself to improve
its execution
self-organizing function: function that includes processes which require minimum manual intervention
self-regulation: capability of a component or system to regulate its internal parameters so as to assure a quality-of-
service metric such as reliability, precision, rapidity, or throughput
3.2 Symbols
Void.
3.3 Abbreviations
For the purposes of the present document, the following abbreviations apply:
rd
3GPP 3 Generation Partnership Project
AB Autonomic Behaviour
AF Autonomic Function
AFI Autonomic network engineering for the self-managing Future Internet
AI Artificial Intelligence
AMC Autonomic Management & Control
AN Access Node
ANS Autonomic Nervous System
ETSI
11 ETSI TR 103 626 V1.1.1 (2020-02)
API Application Programming Interface
ARM Advanced RISC Machine
BBF BroadBand Forum
BSS Business Support System
CF Control Framework
CP Control Program
CPU Central Processing Unit
C-SON Centralized Self Organizing Network
DE Decision making Element
DeMe Rfp_GANA-Level2&3-AccessToProtocolsAndMechanisms
DME Decision making Element
E2E End to End
EC European Commission
EMS Element Management System
FlowDesc Flow Description
F-MBTS Federation MBTS
FMM Rfp_FederationMBTS- to-FederationMBTS
FOO Rfp_ONIX-to-ONIX
FPGA Field Programmable Gate Array
FuDe Rfp_FunctionLevelDE-to-FunctionLevelDE
GANA Generic Autonomic Network Architecture
GCP Global Control Program
GITAR Generic extension for Internet-of-Things Architectures
G-MBTS Gouvernance MBTS
GNU radio GNU's Not Unix™ radio
GoS Rfp_OSS_to_Governance-MBTS
GPS Global Positioning System
IBN Intent Based network
INT Core Network and Interoperability Testing
IP Internet Protocol
IPFIX Internet Protocol Flow Information eXport
IPv6 Internet Protocol version 6
IRIS Implementing Radio In Software
KP Knowledge Plane
KP DE Knowledge Plane Decision-making Element
LAN Local Area Network
LQI Link Quality Indicator
LTE Long Term Evolution
MAC Medium Access Control
MBTS Model Based Translation Service
MCE Monitor and Configuration Engine
ME Managed Entity
ME-to-DE reference point ME to DE
MIB Management Information Base
MIPS Microprocessor without Interlocked Pipelined Stages
MO Managed Object
NBI NorthBound Interface
NOTE: See Figures 11 and 12.
NDPI Native Device Programming Interface
NE Network Element
NeDe Rfp_NetworkLevelDE-to-NetworkLevelDE
NeI Rfp_NetworkLevelDE-to-ONIX-System
NeM Rfp_EMS_OR_NMS-to-NodeMainDE
NeMe Rfp_NetworkLevelDE-to-NodeMainDE
NF Network Function
NFV Network Function Virtualisation
NIC Network Interface Card
NMS Network Management System
NoDe Rfp_NodeMainDE-to-NodeMainDE
NoI Rfp_NodeMainDE-to-ONIX-System
ETSI
12 ETSI TR 103 626 V1.1.1 (2020-02)
NTP Network Time Protocol
ONAP Open Networking Automation Platform
ONIX Overlay Network for Information eXchange
OODA Observe, Orient, Decide and Act Loop
OR logical OR symbol
ORCA Orchestration and Reconfiguration Control Architecture
OS Operating System
OsDE reference point OSS knowledge plane Decision-making Element
OsDe Rfp_OSS-to-Network-Level-Des
OSI Open Systems Interconnection
OsI Rfp_OSS-to-ONIX-System (Network Governance Reference Point: OSS/BSS to ONIX)
(Knowledge Plane)
OSi Rfp_OSS-to-ONIX-System (Network Governance Reference Point: OSS/BSS to ONIX)
(Knowledge Plane)
OSS Operation Support System
PC Personal Computer
PER Packet Error Rate
PHY Physical
PoC Proof of Concept
PON Passive Optical Network
PRR Packet Received Rate
PTP Precision Time Protocol
QoS Quality of Service
RAN Radio Access Network
RAS Reconfigurable Antenna Systems
RAT Radio Access Technology
RF Radio Frequency
RISC Reduced Instruction Set Computing
RRH Remote Radio Head
RSSI Received Signal Strength (power) Indication
SDN Software Defined Networks
SDR Software Defined Radio
SNMP Simple Network Management Protocol
SON Self Organizing Networks
TAISC Time Annotated Instruction Set Computer
TB Technical Body
TC Technical Committee
TCP/IP Transfer Control Protocol/Internet Protocol
TDMA Time Division Multiple Access
UPI Unified Programming Interface
UPI_G Unified Programming Interface Global
UPI_HC Unified Programming Interface Hierarchical Control
UPI_M Unified Programming Interface Management
UPI_N Unified Programming Interface Network
UPI_R Unified Programming Interface Radio
USRP Universal Software Radio Peripheral
VoIP Voice over IP
WARP Wireless open-Access Research Platform
WG Working Group
WiFi™ IEEE 802.11™ family of standards
WiSHFUL Wireless Software and Hardware platforms for Flexible and Unified radio and network controL
WLAN Wireless Local Area Network
WMP Wireless MAC Processor
WSN Wireless Sensor Network
xDSL any Digital Subscriber Line
XFSM eXtended Finite State Machines
xPON any PON
ZRE ZeroMQ Realtime Exchange protocol
ETSI
13 ETSI TR 103 626 V1.1.1 (2020-02)
4 Principles for Autonomic Networking and Enablers
4.1 Overview on Autonomics Principles and Enablers, and
introduction to the emerging concept of "Network
compartmentation"
Autonomic networking paradigm aims at creating self-managing networks to overcome the rapidly growing complexity
of current networks and future networks. The complexity aspect of particular concern is management and control of the
networks and services they are required to deliver to various service consumers. Management complexity can be
characterized by factors such as huge number of devices, services to be provisioned and assured, and configuration
parameters of network resources that need to be configured and dynamically optimized to cope with various workloads
and challenges the networks encounter daily during their operations, e.g. manifestations of faults/errors/failures/security
threats and performance degradations on various network resources. The autonomic networking paradigm is the enabler
for self-driving and self-aware networks and services.
Autonomic networking mimics biological autonomic systems, especially those complex life forms that are provided
with an Autonomic Nervous System (ANS) that is not consciously controlled. Analogously to biological systems,
current networks require a conscious control that is mimicked by a centralized network control where a central entity
(the brain), receives information from the peripheral elements, knows the status of the whole system, takes decisions
and finally applies actions by sending commands to peripheral actuators (muscles). Biological and networking
components share such general principles. However, in many applications in wireless networks, the timing for decisions
is not compatible with latencies due to the loop from the peripheral sensor to the central intelligence and back to
peripheral actuators. In such a case, as discussed in clause 5.5, forms of control by delegation has to be taken into
account. The ETSI GANA standard takes into consideration this issue.
Autonomic systems require specific capabilities that appear to be in common with current trends in networks, especially
with wireless networks. These capabilities (functions) include:
• Autognostic capabilities (self-discovery, awareness, and analysis).
• Control capabilities on network elements and interfaces.
• Capabilities to define and verify performance and constraints.
• Capabilities to identify attacks and run defending actions.
The WiSHFUL project does not deliberately aim at creating autonomic networks because it is focused on radio and
network control for experimentation in wireless networks. However, it appears that WiSHFUL naturally fulfils most of
the principles indicated above and provides key enablers for autonomic networks. The ETSI GANA architectural
Reference Model for Autonomic Networking, Cognitive Networking and Self-Management of Networks and Services
(ETSI TS 103 195-2 [i.9]) is purposely designed for autonomic networks and is fully specified in the ETSI standard
ETSI TS 103 195-2 [i.9] (while a brief introduction to the GANA model is also provided later in the present document);
it defines high-level requirements and architectural components for self-management networks. Conversely, WiSHFUL
architecture provides the low-level requirements for wireless autonomic networks, which also map well to the GANA
framework; in fact, the project defines programmability models and control models for radio and network components.
GANA Autonomic Management and Control (AMC) software modules called Decision-making-Elements (DEs) are
meant to be designed in such a way that they employ such models in driving autonomics in a Network
Element/Function (NE/NF) and in the outer realm (the management and control systems realm) overlay. For more
details on this subject clause 4.6 of the present document discusses the GANA abstractions levels for autonomicity
(autonomic/self-management functionality) and how they complement each other.
NOTE 1: The present document aims to illustrate to autonomics implementers how to use WiSHFUL components
and components from the ORCA project as well, to implement the GANA framework's multi-layer
autonomics in order to realize autonomic management and control of heterogeneous wireless access
technologies using cognitive algorithms.
NOTE 2: WiSHFUL provides platforms, tools and architectural elements for wireless experimentation. WiSHFUL
does not take into account security, and the experimental environment is considered trusted. No detection
of misbehaving nodes is implemented and autonomic capabilities of self-defence are out of scope for the
WiSHFUL project.
ETSI
14 ETSI TR 103 626 V1.1.1 (2020-02)
NOTE 3: WiSHFUL supports most of the key enablers for autonomic networks: network compartmentation,
function atomization and composition, closed control loop, context recognition and adaptation, which are
discussed in the following clauses.
Network compartmentation: Network compartmentation is an emerging concept to consider in networking, e.g. in
relation to another concept called network slicing. However, note that Network compartmentation is not taken into
account in WiSHFUL.
WiSHFUL addresses several communication contexts with heterogeneity in devices, technologies, programmability
logic.
4.2 Function atomization
The emerging quest for wireless access flexibility and adaptability requires programmable services, devised to
customize the wireless access operations according to specific network and application scenarios instead of
implementing a specific MAC protocol stack.
These services are composed by simpler primitives: elementary non-programmable functionalities that are natively
provided by the system. Primitives deal with low-level atomic actions such as the physical transmission and reception
of frames. The hierarchical decomposition of traditional MAC/PHY resource control functionalities is preliminary to
introduce programmability at MAC/PHY levels. A well-defined functional decomposition permits to recompose
functions programmatically. Such programs permit to shift from configurability obtained by tuning parameters to
programmability by defining new node behaviours through composed procedures. Atomic decomposition of functions
allows maximal re-composition freedom but, it conversely introduces complexity in composing smaller functional
blocks.
As discussed later in clause 5, WiSHFUL supports several programmable platforms. Most of these platforms pre-
existed WiSHFUL, using the functional decomposition described above. However, WiSHFUL platforms are based on
different technologies; the decomposition in atomic primitives and the functional composition in services has not a
unique form but it depends on the underlying technology, being customized for WSN, WLAN or LTE.
4.3 Function composition
Function composition permits to build flexible, dynamic and autonomic networks. Functional composition requires a
language for linking the atomic functional elements as building blocks to link together. Function composition permits to
define the behavioural logic for wireless nodes both singularly and in groups. Function composition requires also well-
defined application program interfaces for calling the composed services by the radio and network programs.
4.4 Closed control loop (s)
Autonomic networks
...