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Internet Research Task Force (IRTF) CJ. Bernardos
Request for Comments: 8568 UC3M
Category: Informational A. Rahman
ISSN: 2070-1721 InterDigital
JC. Zuniga
SIGFOX
LM. Contreras
TID
P. Aranda
UC3M
P. Lynch
Keysight Technologies
April 2019
Network Virtualization Research Challenges
Abstract
This document describes open research challenges for network
virtualization. Network virtualization is following a similar path
as previously taken by cloud computing. Specifically, cloud
computing popularized migration of computing functions (e.g.,
applications) and storage from local, dedicated, physical resources
to remote virtual functions accessible through the Internet. In a
similar manner, network virtualization is encouraging migration of
networking functions from dedicated physical hardware nodes to a
virtualized pool of resources. However, network virtualization can
be considered to be a more complex problem than cloud computing as it
not only involves virtualization of computing and storage functions
but also involves abstraction of the network itself. This document
describes current research and engineering challenges in network
virtualization including the guarantee of quality of service,
performance improvement, support for multiple domains, network
slicing, service composition, device virtualization, privacy and
security, separation of control concerns, network function placement,
and testing. In addition, some proposals are made for new activities
in the IETF and IRTF that could address some of these challenges.
This document is a product of the Network Function Virtualization
Research Group (NFVRG).
Bernardos, et al. Informational [Page 1]
RFC 8568 Network Virtualization Research Challenges April 2019
Status of This Memo
This document is not an Internet Standards Track specification; it is
published for informational purposes.
This document is a product of the Internet Research Task Force
(IRTF). The IRTF publishes the results of Internet-related research
and development activities. These results might not be suitable for
deployment. This RFC represents the consensus of the Network
Function Virtualization Research Group of the Internet Research Task
Force (IRTF). Documents approved for publication by the IRSG are not
candidates for any level of Internet Standard; see Section 2 of RFC
7841.
Information about the current status of this document, any errata,
and how to provide feedback on it may be obtained at
https://www.rfc-editor.org/info/rfc8568.
Copyright Notice
Copyright (c) 2019 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents
(https://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.
Bernardos, et al. Informational [Page 2]
RFC 8568 Network Virtualization Research Challenges April 2019
Table of Contents
1. Introduction and Scope . . . . . . . . . . . . . . . . . . . 4
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Background . . . . . . . . . . . . . . . . . . . . . . . . . 6
3.1. Network Function Virtualization . . . . . . . . . . . . . 6
3.2. Software-Defined Networking . . . . . . . . . . . . . . . 9
3.3. ITU-T Functional Architecture of SDN . . . . . . . . . . 13
3.4. Multi-Access Edge Computing . . . . . . . . . . . . . . . 15
3.5. IEEE 802.1CF (OmniRAN) . . . . . . . . . . . . . . . . . 15
3.6. Distributed Management Task Force (DMTF) . . . . . . . . 15
3.7. Open-Source Initiatives . . . . . . . . . . . . . . . . . 16
4. Network Virtualization Challenges . . . . . . . . . . . . . . 18
4.1. Overview . . . . . . . . . . . . . . . . . . . . . . . . 18
4.2. Guaranteeing Quality of Service . . . . . . . . . . . . . 18
4.2.1. Virtualization Technologies . . . . . . . . . . . . . 18
4.2.2. Metrics for NFV Characterization . . . . . . . . . . 19
4.2.3. Predictive Analysis . . . . . . . . . . . . . . . . . 20
4.2.4. Portability . . . . . . . . . . . . . . . . . . . . . 20
4.3. Performance Improvement . . . . . . . . . . . . . . . . . 21
4.3.1. Energy Efficiency . . . . . . . . . . . . . . . . . . 21
4.3.2. Improved Link Usage . . . . . . . . . . . . . . . . . 21
4.4. Multiple Domains . . . . . . . . . . . . . . . . . . . . 22
4.5. 5G and Network Slicing . . . . . . . . . . . . . . . . . 22
4.5.1. Virtual Network Operators . . . . . . . . . . . . . . 23
4.5.2. Extending Virtual Networks and Systems to the
Internet of Things . . . . . . . . . . . . . . . . . 24
4.6. Service Composition . . . . . . . . . . . . . . . . . . . 25
4.7. Device Virtualization for End Users . . . . . . . . . . . 27
4.8. Security and Privacy . . . . . . . . . . . . . . . . . . 27
4.9. Separation of Control Concerns . . . . . . . . . . . . . 29
4.10. Network Function Placement . . . . . . . . . . . . . . . 29
4.11. Testing . . . . . . . . . . . . . . . . . . . . . . . . . 30
4.11.1. Changes in Methodology . . . . . . . . . . . . . . . 30
4.11.2. New Functionality . . . . . . . . . . . . . . . . . 31
4.11.3. Opportunities . . . . . . . . . . . . . . . . . . . 32
5. Technology Gaps and Potential IETF Efforts . . . . . . . . . 33
6. NFVRG Focus Areas . . . . . . . . . . . . . . . . . . . . . . 34
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 35
8. Security Considerations . . . . . . . . . . . . . . . . . . . 35
9. Informative References . . . . . . . . . . . . . . . . . . . 35
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 41
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 41
Bernardos, et al. Informational [Page 3]
RFC 8568 Network Virtualization Research Challenges April 2019
1. Introduction and Scope
The telecommunications sector is experiencing a major revolution that
will shape the way networks and services are designed and deployed
for the next few decades. In order to cope with continuously
increasing demand and cost, network operators are taking lessons from
the IT paradigm of cloud computing. This new approach of
virtualizing network functions will enable multi-fold advantages by
moving communication services from bespoke hardware in the operator's
core network to Commercial Off-The-Shelf (COTS) equipment distributed
across data centers.
Some of the network virtualization mechanisms that are being
considered include the following: sharing of network infrastructure
to reduce costs, virtualization of core and edge servers/services
running in data centers as a way of supporting their load-aware
elastic dimensioning, and dynamic energy policies to reduce the
electricity consumption.
This document presents research and engineering challenges in network
virtualization that need to be addressed in order to achieve these
goals, spanning from pure research and engineering/standards space.
The objective of this memo is to document the technical challenges
and corresponding current approaches and to expose requirements that
should be addressed by future research and standards work.
This document represents the consensus of the Network Function
Virtualization Research Group (NFVRG). It has been reviewed by the
RG members active in the specific areas of work covered by the
document.
2. Terminology
The following terms used in this document are defined by the ETSI
Network Function Virtualization (NFV) Industrial Study Group (ISG)
[etsi_gs_nfv_003], the Open Networking Foundation (ONF) [onf_tr_521],
and the IETF [RFC7426] [RFC7665]:
Application Plane: The collection of applications and services that
program network behavior.
Control Plane (CP): The collection of functions responsible for
controlling one or more network devices. The CP instructs network
devices with respect to how to process and forward packets. The
control plane interacts primarily with the forwarding plane and,
to a lesser extent, with the operational plane.
Bernardos, et al. Informational [Page 4]
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Forwarding Plane (FP): The collection of resources across all
network devices responsible for forwarding traffic.
Management Plane (MP): The collection of functions responsible for
monitoring, configuring, and maintaining one or more network
devices or parts of network devices. The management plane is
mostly related to the operational plane (it is related less to the
forwarding plane).
NFV Infrastructure (NFVI): Totality of all hardware and software
components that build up the environment in which VNFs are
deployed.
NFV Management and Orchestration (NFV-MANO): Functions collectively
provided by NFVO, VNFM, and VIM.
NFV Orchestrator (NFVO): Functional block that manages the Network
Service (NS) life cycle and coordinates the management of NS life
cycle, VNF life cycle (supported by the VNFM) and NFVI resources
(supported by the VIM) to ensure an optimized allocation of the
necessary resources and connectivity.
Operational Plane (OP): The collection of resources responsible for
managing the overall operation of individual network devices.
Physical Network Function (PNF): Physical implementation of a
network function in a monolithic realization.
Service Function Chain (SFC): For a given service, the abstracted
view of the required service functions and the order in which they
are to be applied. This is somehow equivalent to the Network
Function Forwarding Graph (NF-FG) at ETSI.
Service Function Path (SFP): The selection of specific service
function instances on specific network nodes to form a service
graph through which an SFC is instantiated.
Virtualized Infrastructure Manager (VIM): Functional block that is
responsible for controlling and managing the NFVI compute,
storage, and network resources, usually within one infrastructure
operator's domain.
Virtualized Network Function (VNF): Implementation of a Network
Function that can be deployed on a Network Function Virtualization
Infrastructure (NFVI).
Virtualized Network Function Manager (VNFM): Functional block that
is responsible for the life-cycle management of VNF.
Bernardos, et al. Informational [Page 5]
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3. Background
This section briefly describes some basic background technologies as
well as other Standards Developing Organizations (SDOs) and open-
source initiatives working on network virtualization or related
topics.
3.1. Network Function Virtualization
The ETSI ISG Network Function Virtualization (NFV) is a working group
that, since 2012, has aimed to evolve quasi-standard IT
virtualization technology to consolidate many network equipment types
into industry standard high-volume servers, switches, and storage.
It enables implementing network functions in software that can run on
a range of industry-standard server hardware and can be moved to, or
loaded in, various locations in the network as required, without the
need to install new equipment. The ETSI NFV is one of the
predominant NFV reference framework and architectural footprints
[nfv_sota_research_challenges]. The ETSI NFV framework architecture
is composed of three domains (Figure 1):
o Virtualized Network Function, running over the NFVI.
o NFVI, including the diversity of physical resources and how these
can be virtualized. NFVI supports the execution of the VNFs.
o NFV Management and Orchestration, which covers the orchestration
and life-cycle management of physical and/or software resources
that support the infrastructure virtualization, and the life-cycle
management of VNFs. NFV Management and Orchestration focuses on
all virtualization-specific management tasks necessary in the NFV
framework.
Bernardos, et al. Informational [Page 6]
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+-------------------------------------------+ +---------------+
| Virtualized Network Functions (VNFs) | | |
| ------- ------- ------- ------- | | |
| | | | | | | | | | | |
| | VNF | | VNF | | VNF | | VNF | | | |
| | | | | | | | | | | |
| ------- ------- ------- ------- | | |
+-------------------------------------------+ | |
| |
+-------------------------------------------+ | |
| NFV Infrastructure (NFVI) | | NFV |
| ----------- ----------- ----------- | | Management |
| | Virtual | | Virtual | | Virtual | | | and |
| | Compute | | Storage | | Network | | | Orchestration |
| ----------- ----------- ----------- | | |
| +---------------------------------------+ | | |
| | Virtualization Layer | | | |
| +---------------------------------------+ | | |
| +---------------------------------------+ | | |
| | ----------- ----------- ----------- | | | |
| | | Compute | | Storage | | Network | | | | |
| | ----------- ----------- ----------- | | | |
| | Hardware resources | | | |
| +---------------------------------------+ | | |
+-------------------------------------------+ +---------------+
Figure 1: ETSI NFV Framework
The NFV architectural framework identifies functional blocks and the
main reference points between such blocks. Some of these are already
present in current deployments, whilst others might be necessary
additions in order to support the virtualization process and
consequent operation. The functional blocks are (Figure 2):
o Virtualized Network Function (VNF)
o Element Management (EM)
o NFV Infrastructure, including: Hardware and virtualized resources
as well as the Virtualization Layer.
o Virtualized Infrastructure Manager(s) (VIM)
o NFV Orchestrator
o VNF Manager(s)
o Service, VNF and Infrastructure Description
Bernardos, et al. Informational [Page 7]
RFC 8568 Network Virtualization Research Challenges April 2019
o Operational Support Systems and Business Support Systems (OSS and
BSS)
+--------------------+
+-------------------------------------------+ | ---------------- |
| OSS/BSS | | | NFV | |
+-------------------------------------------+ | | Orchestrator +-- |
| ---+------------ | |
+-------------------------------------------+ | | | |
| --------- --------- --------- | | | | |
| | EM 1 | | EM 2 | | EM 3 | | | | | |
| ----+---- ----+---- ----+---- | | ---+---------- | |
| | | | |--|-| VNF | | |
| ----+---- ----+---- ----+---- | | | manager(s) | | |
| | VNF 1 | | VNF 2 | | VNF 3 | | | ---+---------- | |
| ----+---- ----+---- ----+---- | | | | |
+------|-------------|-------------|--------+ | | | |
| | | | | | |
+------+-------------+-------------+--------+ | | | |
| NFV Infrastructure (NFVI) | | | | |
| ----------- ----------- ----------- | | | | |
| | Virtual | | Virtual | | Virtual | | | | | |
| | Compute | | Storage | | Network | | | | | |
| ----------- ----------- ----------- | | ---+------ | |
| +---------------------------------------+ | | | | | |
| | Virtualization Layer | |--|-| VIM(s) +-------- |
| +---------------------------------------+ | | | | |
| +---------------------------------------+ | | ---------- |
| | ----------- ----------- ----------- | | | |
| | | Compute | | Storage | | Network | | | | |
| | | hardware| | hardware| | hardware| | | | |
| | ----------- ----------- ----------- | | | |
| | Hardware resources | | | NFV Management |
| +---------------------------------------+ | | and Orchestration |
+-------------------------------------------+ +--------------------+
Figure 2: ETSI NFV Reference Architecture
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3.2. Software-Defined Networking
The Software-Defined Networking (SDN) paradigm pushes the
intelligence currently residing in the network elements to a central
controller implementing the network functionality through software.
In contrast to traditional approaches, in which the network's control
plane is distributed throughout all network devices, with SDN, the
control plane is logically centralized. In this way, the deployment
of new characteristics in the network no longer requires complex and
costly changes in equipment or firmware updates, but only a change in
the software running in the controller. The main advantage of this
approach is the flexibility it provides operators to manage their
network, i.e., an operator can easily change its policies on how
traffic is distributed throughout the network.
One of the most well-known protocols for the SDN control plane
between the central controller and the networking elements is the
OpenFlow Protocol (OFP), which is maintained and extended by the Open
Network Foundation (ONF) <https://www.opennetworking.org/>.
Originally, this protocol was developed specifically for IEEE 802.1
switches conforming to the ONF OpenFlow Switch specification
[OpenFlow]. As the benefits of the SDN paradigm have reached a wider
audience, its application has been extended to more complex scenarios
such as wireless and mobile networks. Within this area of work, the
ONF is actively developing new OFP extensions addressing three key
scenarios: (i) wireless backhaul, (ii) cellular Evolved Packet Core
(EPC), and (iii) unified access and management across enterprise
wireless and fixed networks.
Bernardos, et al. Informational [Page 9]
RFC 8568 Network Virtualization Research Challenges April 2019
+----------+
| ------- |
| |Oper.| | O
| |Mgmt.| |<........> -+- Network Operator
| |Iface| | ^
| ------- | +----------------------------------------+
| | | +------------------------------------+ |
| | | | --------- --------- --------- | |
|--------- | | | | App 1 | | App 2 | ... | App n | | |
||Plugins| |<....>| | --------- --------- --------- | |
|--------- | | | Plugins | |
| | | +------------------------------------+ |
| | | Application Plane |
| | +----------------------------------------+
| | A
| | |
| | V
| | +----------------------------------------+
| | | +------------------------------------+ |
|--------- | | | ------------ ------------ | |
|| Netw. | | | | | Module 1 | | Module 2 | | |
||Engine | |<....>| | ------------ ------------ | |
|--------- | | | Network Engine | |
| | | +------------------------------------+ |
| | | Control Plane |
| | +----------------------------------------+
| | A
| | |
| | V
| | +----------------------------------------+
| | | +--------------+ +--------------+ |
| | | | ------------ | | ------------ | |
|----------| | | | OpenFlow | | | | OpenFlow | | |
||OpenFlow||<....>| | ------------ | | ------------ | |
|----------| | | NE | | NE | |
| | | +--------------+ +--------------+ |
| | | Data Plane |
|Management| +----------------------------------------+
+----------+
Figure 3: High-Level SDN ONF Architecture
Figure 3 shows the blocks and the functional interfaces of the ONF
architecture, which comprises three planes: data, controller, and
application. The data plane comprehends several Network Entities
(NEs), which expose their capabilities toward the control plane via a
Southbound API. The control plane includes several cooperating
modules devoted to the creation and maintenance of an abstracted
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resource model of the underlying network. Such a model is exposed to
the applications via a Northbound API where the application plane
comprises several applications/services, each of which has exclusive
control of a set of exposed resources.
The management plane spans its functionality across all planes
performing the initial configuration of the network elements in the
data plane, the assignment of the SDN controller and the resources
under its responsibility. In the control plane, the management needs
to configure the policies defining the scope of the control given to
the SDN applications, to monitor the performance of the system and to
configure the parameters required by the SDN controller modules. In
the application plane, the management plane configures the parameters
of the applications and the service-level agreements. In addition to
these interactions, the management plane exposes several functions to
network operators that can easily and quickly configure and tune the
network at each layer.
In RFC 7426 [RFC7426], the IRTF Software-Defined Networking Research
Group (SDNRG) documented a layer model of an SDN architecture. This
was due to the following controversial discussion topics (among
others). What exactly is SDN? What is the layer structure of the
SDN architecture? How do layers interface with each other?
Figure 4 reproduces the figure included in RFC 7426 [RFC7426] to
summarize the SDN architecture abstractions in the form of a
detailed, high-level schematic. In a particular implementation,
planes can be collocated with other planes or can be physically
separated.
In SDN, a controller manipulates controlled entities via an
interface. Interfaces, when local, are mostly API invocations
through some library or system call. However, such interfaces may be
extended via some protocol definition, which may use local
interprocess communication (IPC) or a protocol that could also act
remotely; the protocol may be defined as an open standard or in a
proprietary manner.
SDN expands multiple planes: forwarding, operational, control,
management, and application. All planes mentioned above are
connected via interfaces. Additionally, RFC 7426 [RFC7426] considers
four abstraction layers: the Device and resource Abstraction Layer
(DAL), the Control Abstraction Layer (CAL), the Management
Abstraction Layer (MAL), and the Network Services Abstraction Layer
(NSAL).
Bernardos, et al. Informational [Page 11]
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o--------------------------------o
| |
| +-------------+ +----------+ |
| | Application | | Service | |
| +-------------+ +----------+ |
| Application Plane |
o---------------Y----------------o
|
*-----------------------------Y---------------------------------*
| Network Services Abstraction Layer (NSAL) |
*------Y------------------------------------------------Y-------*
| |
| Service Interface |
| |
o------Y------------------o o---------------------Y------o
| | Control Plane | | Management Plane | |
| +----Y----+ +-----+ | | +-----+ +----Y----+ |
| | Service | | App | | | | App | | Service | |
| +----Y----+ +--Y--+ | | +--Y--+ +----Y----+ |
| | | | | | | |
| *----Y-----------Y----* | | *---Y---------------Y----* |
| | Control Abstraction | | | | Management Abstraction | |
| | Layer (CAL) | | | | Layer (MAL) | |
| *----------Y----------* | | *----------Y-------------* |
| | | | | |
o------------|------------o o------------|---------------o
| |
| CP | MP
| Southbound | Southbound
| Interface | Interface
| |
*------------Y---------------------------------Y----------------*
| Device and resource Abstraction Layer (DAL) |
*------------Y---------------------------------Y----------------*
| | | |
| o-------Y----------o +-----+ o--------Y----------o |
| | Forwarding Plane | | App | | Operational Plane | |
| o------------------o +-----+ o-------------------o |
| Network Device |
+---------------------------------------------------------------+
Figure 4: SDN-Layer Architecture
While SDN is often directly associated to OpenFlow, this is just one
(relevant) example of a southbound protocol between the central
controller and the network entities. Other relevant examples of
protocols in the SDN family are NETCONF [RFC6241], RESTCONF
[RFC8040], and ForCES [RFC5810].
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3.3. ITU-T Functional Architecture of SDN
The ITU-T (the Telecommunication standardization sector of the
International Telecommunication Union) has also looked into SDN
architectures, defining a slightly modified one from what other SDOs
have done. In ITU-T recommendation Y.3302 [itu-t-y.3302], the ITU-T
provides a functional architecture of SDN with descriptions of
functional components and reference points. The described functional
architecture is intended to be used as an enabler for further studies
on other aspects such as protocols and security as well as being used
to customize SDN in support of appropriate use cases (e.g., cloud
computing, mobile networks). This recommendation is based on ITU-T
Y.3300 [itu-t-y.3300] and ITU-T Y.3301 [itu-t-y.3301]. While the
first describes the framework of SDN (including definitions,
objectives, high-level capabilities, requirements, and the high-level
architecture of SDN), the second describes more-detailed
requirements.
Figure 5 shows the SDN functional architecture defined by the ITU-T.
It is a layered architecture composed of the SDN application layer
(SDN-AL), the SDN control layer (SDN-CL), and the SDN resource layer
(SDN-RL). It also has multi-layer management functions (MMF), which
provide the ability to manage the functionalities of SDN layers,
i.e., SDN-AL, SDN-CL, and SDN-RL. MMF interacts with these layers
using Multi-layer Management Functions Application (MMFA), Multi-
layer Management Functions Control (MMFC), and Multi-layer Management
Functions Resource (MMFR) reference points.
The SDN-AL enables a service-aware behavior of the underlying network
in a programmatic manner. The SDN-CL provides programmable means to
control the behavior of SDN-RL resources (such as data transport and
processing) following requests received from the SDN-AL according to
MMF policies. The SDN-RL is where the physical or virtual network
elements perform transport and/or processing of data packets
according to SDN-CL decisions.
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MMFO MMFA
+-----+ . +---------------------+ . +--------------------+
| | . |+---+ +---+ +-------+| . |+---------+ +-----+ |
| | . || | | | | || . || AL. | | | |
| | . || E | | | | App. || . || Mngmt. | | SDN | | SDN-AL
| | . || x | | M | | Layer || . || Support | | App | |
| | . || t.| | u | | Mngmt.|| . || & Orch. | | | |
| | . || | | l | +-------+| . |+---------+ +-----+ |
| | . || R | | t | | . +--------------------+
| | . || e | | i | |MMFC ..................... ACI
| | . || l | | - | | . +--------------------+
| | . || a | | l | +-------+| . |+------+ +---------+|
| OSS/| . || t | | a | | || . || | | App. ||
| BSS | . || i | | y | | || . || | | Support ||
| | . || o | | e | | || . || | +---------+|
| | . || n | | r | | || . || CL | +---------+|
| | . || s | | | |Control|| . ||Mngmt.| | Control ||
| | . || h | | M | | Layer || . || Supp.| | Layer || SDN-CL
| | . || i | | a | | Mngmt.|| . || and | | Serv. ||
| | . || p | | n | | || . || Orch.| +---------+|
| | . || | | a | | || . || | +---------+|
| | . || M | | g | | || . || | | Resource||
| | . || n | | e | | || . || | | Abstrac.||
| | . || g | | m | +-------+| . |+------+ +---------+|
| | . || m | | e | | . +--------------------+
| | . || t.| | n | |MMFR ..................... RCI
| | . || | | t | | . +--------------------+
+-----+ . |+---+ | | +-------+| . |+------++----------+|
| | O | | || . || ||RL Control||
| | r | |Resour.|| . || RL |+----------+|
MMF | | c | | Layer || . ||Mngmt.|+----++----+| SDN-RL
| | h.| | Mngmt.|| . || Supp.||Data||Data||
| | | | || . || ||Tran||Proc||
| +---+ +-------+| . |+------++----++----+|
+---------------------+ . +--------------------+
Legend:
ACI: Application Control Interface
MMFA: Multi-layer Management Functions Application
MMFC: Multi-layer Management Functions Control
MMFO: Multi-layer Management Functions OSS/BSS
MMFR: Multi-layer Management Functions Resource
RCI: Resource Control Interfaces
RL: Resource Layer
Figure 5: ITU-T SDN Functional Architecture
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3.4. Multi-Access Edge Computing
Multi-access Edge Computing (MEC) -- formerly known as Mobile Edge
Computing -- capabilities deployed in the edge of the mobile network
can facilitate the efficient and dynamic provision of services to
mobile users. The ETSI ISG MEC working group, operative from end of
2014, intends to specify an open environment for integrating MEC
capabilities with service providers' networks, also including
applications from third parties. These distributed computing
capabilities provide IT infrastructure as in a cloud environment for
the deployment of functions in mobile access networks. It can be
seen then as a complement to both NFV and SDN.
3.5. IEEE 802.1CF (OmniRAN)
The IEEE 802.1CF Recommended Practice [omniran] specifies an access
network that connects terminals to their access routers utilizing
technologies based on the family of IEEE 802 Standards (e.g., 802.3
Ethernet, 802.11 Wi-Fi, etc.). The specification defines an access
network reference model, including entities and reference points
along with behavioral and functional descriptions of communications
among those entities.
The goal of this project is to help unify the support of different
interfaces, enabling shared-network control and use of SDN
principles, thereby lowering the barriers to new network
technologies, to new network operators, and to new service providers.
3.6. Distributed Management Task Force (DMTF)
The DMTF <https://www.dmtf.org/> is an industry standards
organization working to simplify the manageability of network-
accessible technologies through open and collaborative efforts by
some technology companies. The DMTF is involved in the creation and
adoption of interoperable management standards, supporting
implementations that enable the management of diverse traditional and
emerging technologies including cloud, virtualization, network, and
infrastructure.
There are several DMTF initiatives that are relevant to the network
virtualization area, such as the Open Virtualization Format (OVF) for
VNF packaging; the Cloud Infrastructure Management Interface (CIMI)
for cloud infrastructure management; the Network Management (NETMAN),
for VNF management; and the Virtualization Management (VMAN), for
virtualization infrastructure management.
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3.7. Open-Source Initiatives
The open-source community is especially active in the area of network
virtualization and orchestration. We next summarize some of the
active efforts:
o OpenStack. OpenStack is a free and open-source cloud-computing
software platform. OpenStack software controls large pools of
compute, storage, and networking resources throughout a data
center, managed through a dashboard or via the OpenStack API.
o Kubernetes. Kubernetes is an open-source system for automating
deployment, scaling and management of containerized applications.
Kubernetes can schedule and run application containers on clusters
of physical or virtual machines. Kubernetes allows (i) Scale on
the fly, (ii) Limit hardware usage to required resources only,
(iii) Load-balancing Monitoring, and (iv) Efficient life-cycle
management.
o OpenDayLight. OpenDayLight (ODL) is a highly available, modular,
extensible and scalable multiprotocol controller infrastructure
built for SDN deployments on modern heterogeneous multi-vendor
networks. It provides a model-driven service abstraction platform
that allows users to write apps that easily work across a wide
variety of hardware and southbound protocols.
o ONOS. The Open Network Operating System (ONOS) project is an
open-source community hosted by The Linux Foundation. The goal of
the project is to create an SDN operating system for
communications service providers that is designed for scalability,
high performance, and high availability.
o OpenContrail. OpenContrail is a licensed Apache 2.0 project that
is built using standards-based protocols and that provides all the
necessary components for network virtualization: an SDN
controller, a virtual router, an analytics engine, and published
northbound APIs. It has an extensive Representational State
Transfer (REST) API to configure and gather operational and
analytics data from the system.
o OPNFV. The Open Platform for NFV (OPNFV) is a carrier-grade,
integrated, open-source platform to accelerate the introduction of
new NFV products and services. By integrating components from
upstream projects, the OPNFV community aims at conducting
performance and use case-based testing to ensure the platform's
suitability for NFV use cases. The scope of OPNFV's initial
release is focused on building NFV Infrastructure (NFVI) and
Virtualized Infrastructure Manager (VIM) by integrating components
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from upstream projects such as OpenDayLight, OpenStack, Ceph
Storage, Kernel-based Virtual Machine (KVM), Open vSwitch, and
Linux. These components, along with APIs to other NFV elements,
form the basic infrastructure required for Virtualized Network
Functions (VNFs) and Management and Orchestration (MANO)
components. OPNFV's goal is to (i) increase performance and power
efficiency, (ii) improve reliability, availability, and
serviceability, and (iii) deliver comprehensive platform
instrumentation.
o OSM. Open Source Mano (OSM) is an ETSI-hosted project to develop
an Open Source NFV Management and Orchestration (MANO) software
stack aligned with ETSI NFV. OSM is based on components from
previous projects, such Telefonica's OpenMANO or Canonical's Juju,
among others.
o OpenBaton. OpenBaton is a Network Function Virtualization
Orchestrator (NFVO) that is ETSI NFV compliant. OpenBaton was
part of the OpenSDNCore project started with the objective of
providing a compliant implementation of the ETSI NFV
specification.
o ONAP. Open Network Automation Platform (ONAP) is an open-source
software platform that delivers capabilities for the design,
creation, orchestration, monitoring, and life-cycle management of
(i) Virtual Network Functions (VNFs), (ii) The carrier-scale
Software-Defined Networks (SDNs) that contain them, and (iii)
higher-level services that combine the above. ONAP (derived from
the AT&T's ECOMP) provides for automatic, policy-driven
interaction of these functions and services in a dynamic, real-
time cloud environment.
o SONA. The Simplified Overlay Network Architecture (SONA) is an
extension to ONOS to have an almost full SDN network control in
OpenStack for virtual tenant network provisioning. Basically,
SONA is an SDN-based network virtualization solution for cloud DC.
Among the main areas that are being developed by the aforementioned
open-source activities that relate to network virtualization
research, we can highlight policy-based resource management,
analytics for visibility and orchestration, and service verification
with regard to security and resiliency.
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4. Network Virtualization Challenges
4.1. Overview
Network virtualization is changing the way the telecommunications
sector will deploy, extend, and operate their networks. These new
technologies aim at reducing the overall costs by moving
communication services from specific hardware in the operators' cores
to server farms scattered in data centers (i.e., compute and storage
virtualization). In addition, the networks interconnecting the
functions that compose a network service are fundamentally affected
in the way they route, process, and control traffic (i.e., network
virtualization).
4.2. Guaranteeing Quality of Service
Achieving a given QoS in an NFV environment with virtualized and
distributed computing, storage, and networking functions is more
challenging than providing the equivalent in discrete non-virtualized
components. For example, ensuring a guaranteed and stable forwarding
data rate has proven not to be straightforward when the forwarding
function is virtualized and runs on top of COTS server hardware
[openmano_dataplane] [NFV-COTS] [etsi_nfv_whitepaper_3]. Again, the
comparison point is against a router or forwarder built on optimized
hardware. We next identify some of the challenges that this poses.
4.2.1. Virtualization Technologies
The issue of guaranteeing a network QoS is less of an issue for
"traditional" cloud computing because the workloads that are treated
there are servers or clients in the networking sense and hardly ever
process packets. Cloud computing provides hosting for applications
on shared servers in a highly separated way. Its main advantage is
that the infrastructure costs are shared among tenants and that the
cloud infrastructure provides levels of reliability that can not be
achieved on individual premises in a cost-efficient way
[intel_10_differences_nfv_cloud]. NFV has very strict requirements
posed in terms of performance, stability, and consistency. Although
there are some tools and mechanisms to improve this, such as Enhanced
Performance Awareness (EPA), Single Root I/O Virtualization (SR-IOV),
Non-Uniform Memory Access (NUMA), Data Plane Development Kit (DPDK),
etc., these are still unsolved challenges. One open research issue
is finding out technologies that are different from Virtual Machines
(VMs) and more suitable for dealing with network functionalities.
Lately, a number of lightweight virtualization technologies including
containers, unikernels (specialized VMs) and minimalistic
distributions of general-purpose OSes have appeared as virtualization
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approaches that can be used when constructing an NFV platform.
[LIGHT-NFV] describes the challenges in building such a platform and
discusses to what extent these technologies, as well as traditional
VMs, are able to address them.
4.2.2. Metrics for NFV Characterization
Another relevant aspect is the need for tools for diagnostics and
measurements suited for NFV. There is a pressing need to define
metrics and associated protocols to measure the performance of NFV.
Specifically, since NFV is based on the concept of taking centralized
functions and evolving them to highly distributed software (SW)
functions, there is a commensurate need to fully understand and
measure the baseline performance of such systems.
The IP Performance Metrics (IPPM) WG defines metrics that can be used
to measure the quality and performance of Internet services and
applications running over transport-layer protocols (e.g., TCP and
UDP) over IP. It also develops and maintains protocols for the
measurement of these metrics. While the IPPM WG is a long-running WG
that started in 1997, at the time of writing, it does not have a
charter item or active Internet-Drafts related to the topic of
network virtualization. In addition to using IPPM to evaluate QoS,
there is a need for specific metrics for assessing the performance of
network-virtualization techniques.
The Benchmarking Methodology Working Group (BMWG) is also performing
work related to NFV metrics. For example, [RFC8172] investigates
additional methodological considerations necessary when benchmarking
VNFs that are instantiated and hosted in general-purpose hardware,
using bare-metal hypervisors or other isolation environments (such as
Linux containers). An essential consideration is benchmarking
physical and VNFs in the same way when possible, thereby allowing
direct comparison.
There is a clear motivation for the work on performance metrics for
NFV [etsi_gs_nfv_per_001], as stated in [RFC8172] (and replicated
here):
I'm designing and building my NFV Infrastructure platform. The
first steps were easy because I had a small number of categories
of VNFs to support and the VNF vendor gave HW recommendations that
I followed. Now I need to deploy more VNFs from new vendors, and
there are different hardware recommendations. How well will the
new VNFs perform on my existing hardware? Which among several new
VNFs in a given category are most efficient in terms of capacity
they deliver? And, when I operate multiple categories of VNFs
(and PNFs) *concurrently* on a hardware platform such that they
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share resources, what are the new performance limits, and what are
the software design choices I can make to optimize my chosen
hardware platform? Conversely, what hardware platform upgrades
should I pursue to increase the capacity of these concurrently
operating VNFs?
Lately, there are also some efforts looking into VNF benchmarking.
The selection of an NFV Infrastructure Point of Presence to host a
VNF or allocation of resources (e.g., virtual CPUs, memory) needs to
be done over virtualized (abstracted and simplified) resource views
[vnf_benchmarking] [VNF-VBAAS].
4.2.3. Predictive Analysis
On top of diagnostic tools that enable an assessment of the QoS,
predictive analyses are required to react before anomalies occur.
Due to the SW characteristics of VNFs, a reliable diagnosis framework
could potentially enable the prevention of issues by a proper
diagnosis and then a reaction in terms of acting on the potentially
impacted service (e.g., migration to a different compute node,
scaling in/out, up/down, etc.).
4.2.4. Portability
Portability in NFV refers to the ability to run a given VNF on
multiple NFVIs, that is, guaranteeing that the VNF would be able to
perform its functions with a high and predictable performance given
that a set of requirements on the NFVI resources is met. Therefore,
portability is a key feature that, if fully enabled, would contribute
to making the NFV environment achieve a better reliability than a
traditional system. Implementing functionality in SW over
"commodity" infrastructure should make it much easier to port/move
functions from one place to another. However, this is not yet as
ideal as it sounds, and there are aspects that are not fully tackled.
The existence of different hypervisors, specific hardware
dependencies (e.g., EPA related), or state-synchronization aspects
are just some examples of troublemakers for portability purposes.
The ETSI NFV ISG is doing work in relation to portability.
[etsi_gs_nfv_per_001] provides a list of minimal features that the VM
Descriptor and Compute Host Descriptor should contain for the
appropriate deployment of VM images over an NFVI (i.e., a "telco data
center"), in order to guarantee high and predictable performance of
data-plane workloads while assuring their portability. In addition,
[etsi_gs_nfv_per_001] provides a set of recommendations on the
minimum requirements that hardware (HW) and hypervisor should have
for a "telco data center" suitable for different workloads (data
plane, control plane, etc.) present in VNFs. The purpose of
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[etsi_gs_nfv_per_001] is to provide the list of VM requirements that
should be included in the VM Descriptor template, and the list of HW
capabilities that should be included in the Compute Host Descriptor
(CHD) to assure predictable high performance. ETSI NFV assumes that
the MANO functions will make the mix & match. Therefore, there are
still several research challenges to be addressed here.
4.3. Performance Improvement
4.3.1. Energy Efficiency
Virtualization is typically seen as a direct enabler of energy
savings. Some of the enablers for this that are often mentioned
[nfv_sota_research_challenges] are (i) the multiplexing gains
achieved by centralizing functions in data centers reduce the overall
energy consumed and (ii) the flexibility brought by network
programmability enables to switch off infrastructure as needed in a
much easier way. However, there is still a lot of room for
improvement in terms of virtualization techniques to reduce the power
consumption, such as enhanced-hypervisor technologies.
Some additional examples of research topics that could enable energy
savings are [nfv_sota_research_challenges]:
o Energy-aware scaling (e.g., reductions in CPU speeds and partially
turning off some hardware components to meet a given energy
consumption target.
o Energy-aware function placement.
o Scheduling and chaining algorithms, for example, adapting the
network topology and operating parameters to minimize the
operation cost (e.g., tracking energy costs to identify the
cheapest prices).
Note that it is also important to analyze the trade-off between
energy efficiency and network performance.
4.3.2. Improved Link Usage
The use of NFV and SDN technologies can help improve link usage. SDN
has already shown that it can greatly increase average link
utilization (e.g., Google example [google_sdn_wan]). NFV adds more
complexity (e.g., due to service-function chaining / VNF forwarding
graphs), which needs to be considered. Aspects like the ones
described in [NFVRG-TOPO] (on NFV data center topology design) have
to be looked at carefully as well.
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4.4. Multiple Domains
Market fragmentation has resulted in a multitude of network operators
each focused on different countries and regions. This makes it
difficult to create infrastructure services spanning multiple
countries, such as virtual connectivity or compute resources, as no
single operator has a footprint everywhere. Cross-domain
orchestration of services over multiple administrations or over
multi-domain single administrations will allow end-to-end network and
service elements to mix in multi-vendor, heterogeneous technology,
and resource environments [multi-domain_5GEx].
For the specific use case of 'Network as a Service', it becomes even
more important to ensure that Cross Domain Orchestration also takes
care of hierarchy of networks and their association, with respect to
provisioning tunnels and overlays.
Multi-domain orchestration is currently an active research topic,
which is being tackled, among others, by ETSI NFV ISG and the 5GEx
project <https://www.5gex.eu/> [MULTI-NMRG] [multi-domain_5GEx].
Another side of the multi-domain problem is the integration/
harmonization of different management domains. A key example comes
from Multi-access Edge Computing, which, according to ETSI, comes
with its own MANO system and would require integration if
interconnected to a generic NFV system.
4.5. 5G and Network Slicing
From the beginning of all 5G discussions in the research and industry
fora, it has been agreed that 5G will have to address many more use
cases than the preceding wireless generations, which first focused on
voice services and then on voice and high-speed packet data services.
In this case, 5G should be able to handle not only the same (or
enhanced) voice and packet data services, but also emerging services
like tactile Internet and the Internet of Things (IoT). These use
cases take the requirements to opposite extremes, as some of them
require ultra-low latency and higher-speed, whereas some others
require ultra-low power consumption and high-delay tolerance.
Because of these very extreme 5G use cases, it is envisioned that
selective combinations of radio access networks and core network
components will have to be combined into a given network slice to
address the specific requirements of each use case.
For example, within the major IoT category, which is perhaps the most
disrupting one, some autonomous IoT devices will have very low
throughput, will have much longer sleep cycles (and therefore high
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latency), and a battery life time exceeding by a factor of thousands
that of smartphones or some other devices that will have almost
continuous control and data communications. Hence, it is envisioned
that a customized network slice will have to be stitched together
from virtual resources or sub-slices to meet these requirements.
The actual definition of a "network slice" from an IP infrastructure
viewpoint is currently undergoing intense debate; see [COMS-PS],
[NETSLICES], [SLICE-3GPP], and [ngmn_5G_whitepaper]. Network slicing
is a key for introducing new actors in existing markets at a low cost
-- by letting new players rent "blocks" of capacity, if the new
business model enables performance that meets the application needs
(e.g., broadcasting updates to many sensors with satellite
broadcasting capabilities). However, more work needs to be done to
define the basic architectural approach of how network slices will be
defined and formed. For example, is it mostly a matter of defining
the appropriate network models (e.g., YANG) to stitch the network
slice from existing components? Or do end-to-end timing,
synchronization, and other low-level requirements mean that more
fundamental research has to be done?
4.5.1. Virtual Network Operators
The widespread use/discussion/practice of system and network
virtualization technologies has led to new business opportunities,
enlarging the offer of IT resources with virtual network and
computing resources, among others. As a consequence, the network
ecosystem now differentiates between the owner of physical resources,
the Infrastructure Provider (InP), and the intermediary that conforms
and delivers network services to the final customers, the Virtual
Network Operator (VNO).
VNOs aim to exploit the virtualized infrastructures to deliver new-
and-improved services to their customers. However, current network
virtualization techniques offer poor support for VNOs to control
their resources. It has been considered that the InP is responsible
for the reliability of the virtual resources, but there are several
situations in which a VNO requires a finer control on its resources.
For instance, dynamic events, such as the identification of new
requirements or the detection of incidents within the virtual system,
might urge a VNO to quickly reform its virtual infrastructure and
resource allocation. However, the interfaces offered by current
virtualization platforms do not offer the necessary functions for
VNOs to perform the elastic adaptations they need to conduct in
dynamic environments.
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Beyond their heterogeneity, which can be resolved by software
adapters, current virtualization platforms do not have common methods
and functions, so it is difficult for the virtual network controllers
used by the VNOs to actually manage and control virtual resources
instantiated on different platforms, not even considering different
InPs. Therefore, it is necessary to reach a common definition of the
functions that should be offered by underlying platforms to give such
overlay controllers the possibility to allocate and deallocate
resources dynamically and get monitoring data about them.
Such common methods should be offered by all underlying controllers,
regardless of being network-oriented (e.g., ODL, ONOS, and Ryu) or
computing-oriented (e.g., OpenStack, OpenNebula, and Eucalyptus).
Furthermore, it is important for those platforms to offer some "PUSH"
function to report resource state, avoiding the need for the VNO's
controller to "POLL" for such data. A starting point to get proper
notifications within current REST APIs could be to consider the
protocol proposed by the WEBPUSH WG [RFC8030].
Finally, in order to establish a proper order and allow the
coexistence and collaboration of different systems, a common ontology
regarding network and system virtualization should be defined and
agreed upon, so different and heterogeneous systems can understand
each other without requiring reliance on specific adaptation
mechanisms that might break with any update on any side of the
relation.
4.5.2. Extending Virtual Networks and Systems to the Internet of Things
The Internet of Things (IoT) refers to the vision of connecting a
multitude of automated devices (e.g., lights, environmental sensors,
traffic lights, parking meters, health and security systems, etc.) to
the Internet for purposes of reporting and remote command and control
of the device. This vision is being realized by a multi-pronged
approach of standardization in various forums and complementary open-
source activities. For example, in the IETF, support of IoT web
services has been defined by an HTTP-like protocol adapted for IoT
called "CoAP" [RFC7252]; and, lately, a group has been studying the
need to develop a new network layer to support IP applications over
Low-Power Wide Area Networks (LPWAN).
Elsewhere, for 5G cellular evolution, there is much discussion on the
need for supporting virtual network slices for the expected massive
numbers of IoT devices. A separate virtual network slice is
considered necessary for different 5G IoT use cases because devices
will have very different characteristics than typical cellular
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devices like smartphones [ngmn_5G_whitepaper], and the number of IoT
devices is expected to be at least one or two orders of magnitude
higher than other 5G devices (see Section 4.5).
The specific nature of the IoT ecosystem, particularly reflected in
the Machine-to-Machine (M2M) communications, leads to the creation of
new and highly distributed systems which demand location-based
network and computing services. A specific example can be
represented by a set of "things" that suddenly require the setup of a
firewall to allow external entities to access their data while
outsourcing some computation requirements to more powerful systems
relying on cloud-based services. This representative use case
exposes important requirements for both NFV and the underlying cloud
infrastructures.
In order to provide the aforementioned location-based functions
integrated with highly distributed systems, the so-called fog
infrastructures should be able to instantiate VNFs, placing them in
the required place, e.g., close to their consumers. This requirement
implies that the interfaces offered by virtualization platforms must
support the specification of location-based resources, which is a key
function in those scenarios. Moreover, those platforms must also be
able to interpret and understand the references used by IoT systems
to their location (e.g., "My-AP" or "5BLDG+2F") and also the
specification of identifiers linked to other resources, such as the
case of requiring the infrastructure to establish a link between a
specific Access Point (AP) and a specific virtual computing node. In
summary, the research gap is exact localization of VNFs at far
network edge infrastructure, which is highly distributed and dynamic.
4.6. Service Composition
Current network services deployed by operators often involve the
composition of several individual functions (such as packet
filtering, deep-packet inspection, load-balancing). These services
are typically implemented by the ordered combination of a number of
service functions that are deployed at different points within a
network, not necessarily on the direct data path. This requires
traffic to be steered through the required service functions,
wherever they are deployed [RFC7498].
For a given service, the abstracted view of the required service
functions and the order in which they are to be applied is called
"Service Function Chaining" (SFC) [sfc_challenges], which is called
"Network Function Forwarding Graph" (NF-FG) in ETSI. SFC is
instantiated through the selection of specific service function
instances on specific network nodes to form a service graph: this is
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called a "Service Function Path" (SFP). The service functions may be
applied at any layer within the network protocol stack (network
layer, transport layer, application layer, etc.).
Service composition is a powerful means that can provide significant
benefits when applied in a softwarized network environment. However,
there are many research challenges in this area; for example, the
ones related to composition mechanisms and algorithms to enable load-
balancing and improve reliability. The service composition should
also act as an enabler to gather information across all hierarchies
(underlays and overlays) of network deployments that may span across
multiple operators for faster serviceability, thus facilitating
accomplishing aforementioned goals of "load-balancing and improving
reliability".
As described in [dynamic_chaining], different algorithms can be used
to enable dynamic service composition that optimizes a QoS-based
utility function (e.g., minimizing the latency per-application
traffic flows) for a given composition plan. Such algorithms can
consider the computation capabilities and load status of resources
executing the VNF instances, either deduced through estimations from
historical usage data or collected through real-time monitoring
(i.e., context-aware selection). For this reason, selections should
include references to dynamic information on the status of the
service instance and its constituent elements, i.e., monitoring
information related to individual VNF instances and links connecting
them as well as derived monitoring information at the chain level
(e.g., end-to-end delay). At runtime, if one or more VNF instances
are no longer available or QoS degrades below a given threshold, the
service selection task can be rerun to perform service substitution.
There are different research directions that relate to the previous
point. For example, the use of Integer Linear Programming (ILP)
techniques can be explored to optimize the management of diverse
traffic flows. Deep-machine learning can also be applied to optimize
service chains using information parameters, such as some of the ones
mentioned above. Newer scheduling paradigms, like co-flows, can also
be used.
The SFC working group is working on an architecture for SFC [RFC7665]
that includes the necessary protocols or protocol extensions to
convey the SFC and SFP information to nodes that are involved in the
implementation of service functions and SFCs as well as mechanisms
for steering traffic through service functions.
In terms of actual work items, the SFC WG has not yet considered
working on the management and configuration of SFC components related
to the support of SFC. This part is of special interest for
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operators and would be required in order to actually put SFC
mechanisms into operation. Similarly, redundancy and reliability
mechanisms for SFC are currently not dealt with by any WG in the
IETF. While this was the main goal of the VNFpool BoF efforts, it
still remains unaddressed.
4.7. Device Virtualization for End Users
So far, most of the network softwarization efforts have focused on
virtualizing functions of network elements. While virtualization of
network elements started with the core, mobile-network architectures
are now heavily switching to also virtualize Radio Access Network
(RAN) functions. The next natural step is to get virtualization down
at the level of the end-user device (e.g., virtualizing a smartphone)
[virtualization_mobile_device]. The cloning of a device in the cloud
(central or local) bears attractive benefits to both the device and
network operations alike (e.g., power saving at the device by
offloading computational-heaving functions to the cloud, optimized
networking -- both device-to-device and device-to-infrastructure) for
service delivery through tighter integration of the device (via its
clone in the networking infrastructure). This is, for example, being
explored by the European H2020 ICIRRUS project
<https://www.icirrus-5gnet.eu>.
4.8. Security and Privacy
Similar to any other situations where resources are shared, security
and privacy are two important aspects that need to be taken into
account.
In the case of security, there are situations where multiple service
providers will need to coexist in a virtual or hybrid physical/
virtual environment. This requires attestation procedures amongst
different virtual/physical functions and resources as well as ongoing
external monitoring. Similarly, different network slices operating
on the same infrastructure can present security problems, for
instance, if one slice running critical applications (e.g., support
for a safety system) is affected by another slice running a less
critical application. In general, the minimum common denominator for
security measures on a shared system should be equal to or higher
than the one required by the most-critical application. Multiple and
continuous threat model analysis as well as a DevOps model are
required to maintain a certain level of security in an NFV system.
Simplistically, DevOps is a process that combines multiple functions
into single cohesive teams in order to quickly produce quality
software. Typically, it relies on also applying the Agile
development process, which focuses on (among many things) dividing
large features into multiple, smaller deliveries. One part of this
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is to immediately test the new smaller features in order to get
immediate feedback on errors so that if present, they can be
immediately fixed and redeployed.
On the other hand, privacy refers to concerns about the control of
personal data and the decision of what to reveal to whom. In this
case, the storage, transmission, collection, and potential
correlation of information in the NFV system, for purposes not
originally intended or not known by the user, should be avoided.
This is particularly challenging, as future intentions and threats
cannot be easily predicted and still can be applied on data collected
in the past. Therefore, well-known techniques, such as data
minimization using privacy features as default and allowing users to
opt in/out, should be used to prevent potential privacy issues.
Compared to traditional networks, NFV will result in networks that
are much more dynamic (in function distribution and topology) and
elastic (in size and boundaries). Thus, NFV will require network
operators to evolve their operational and administrative security
solutions to work in this new environment. For example, in NFV, the
network orchestrator will become a key node to provide security
policy orchestration across the different physical and virtual
components of the virtualized network. For highly confidential data,
for example, the network orchestrator should take into account if
certain physical HW of the network is considered to be more secure
(e.g., because it is located in secure premises) than other HW.
Traditional telecom networks typically run under a single
administrative domain controlled by (exactly) one operator. With
NFV, it is expected that in many cases, the telecom operator will now
become a tenant (running the VNFs), and the infrastructure (NFVI) may
be run by a different operator and/or cloud service provider (see
also Section 4.4). Thus, there will be multiple administrative
domains involved, making security policy coordination more complex.
For example, who will be in charge of provisioning and maintaining
security credentials such as public and private keys? Also, should
private keys be allowed to be replicated across the NFV for
redundancy reasons? Alternatively, it can be investigated how to
develop a mechanism that avoids such a security policy coordination,
thus making the system more robust.
On a positive note, NFV may better defend against denial-of-service
(DoS) attacks because of the distributed nature of the network (i.e.,
no single point of failure) and the ability to steer (undesirable)
traffic quickly [etsi_gs_nfv_sec_001]. Also, NFVs that have physical
HW that is distributed across multiple data centers will also provide
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better fault isolation environments. Particularly, this holds true
if each data center is protected separately via firewalls,
Demilitarized Zones (DMZs), and other network-protection techniques.
SDN can also be used to help improve security by facilitating the
operation of existing protocols, such as Authentication,
Authorization and Accounting (AAA). The management of AAA
infrastructures, namely the management of AAA routing and the
establishment of security associations between AAA entities, can be
performed using SDN, as analyzed in [SDN-AAA].
4.9. Separation of Control Concerns
NFV environments offer two possible levels of SDN control. One level
is the need for controlling the NFVI to provide connectivity end-to-
end among VNFs or among VNFs and Physical Network Functions (PNFs).
A second level is the control and configuration of the VNFs
themselves (in other words, the configuration of the network service
implemented by those VNFs), taking advantage of the programmability
brought by SDN. Both control concerns are separated in nature.
However, interaction between both could be expected in order to
optimize, scale, or influence each other.
Clear mechanisms for such interactions are needed in order to avoid
malfunctioning or interference concerns. These ideas are considered
in [etsi_gs_nfv_eve005] and [LAYERED-SDN].
4.10. Network Function Placement
Network function placement is a problem in any kind of network
telecommunications infrastructure. Moreover, the increased degree of
freedom added by network virtualization makes this problem even more
important, and also harder to tackle. Deciding where to place VNFs
is a resource-allocation problem that needs to (or may) take into
consideration quite a few aspects: resiliency, (anti-)affinity,
security, privacy, energy efficiency, etc.
When several functions are chained (typical scenario), placement
algorithms become more complex and important (as described in
Section 4.6). While there has been research on the topic
([nfv_piecing], [dynamic_placement], and [vnf-p]), this still remains
an open challenge that requires more attention. The use of multi-
domains adds another component of complexity to this problem that has
to be considered.
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4.11. Testing
The impacts of network virtualization on testing can be divided into
three groups:
1. Changes in methodology
2. New functionality
3. Opportunities
4.11.1. Changes in Methodology
The largest impact of NFV is the ability to isolate the System Under
Test (SUT). When testing PNFs, isolating the SUT means that all the
other devices that the SUT communicates with are replaced with
simulations (or controlled executions) in order to place the SUT
under test by itself. The SUT may be comprised of one or more
devices. The simulations use the appropriate traffic type and
protocols in order to execute test cases.
As shown in Figure 2, NFV provides a common architecture for all
functions to use. A VNF is executed using resources offered by the
NFVI, which have been allocated using the MANO function. It is not
possible to test a VNF by itself, without the entire supporting
environment present. This fundamentally changes how to consider the
SUT. In the case of a VNF (or multiple VNFs), the SUT is part of a
larger architecture that is necessary in order to run the SUTs.
Therefore, isolation of the SUT becomes controlling the environment
in a disciplined manner. The components of the environment necessary
to run the SUTs that are not part of the SUT itself become the test
environment. In the case of VNFs that are part of the SUT, the NFVI
and MANO become the test environment. The configurations and
policies that guide the test environment should remain constant
during the execution of the tests, and also from test to test.
Configurations such as CPU pinning, NUMA configuration, the SW
versions and configurations of the hypervisor, vSwitch and NICs
should remain constant. The only variables in the testing should be
those controlling the SUT itself. If any configuration in the test
environment is changed from test to test, the results become very
difficult, if not impossible, to compare since the test environment
behavior may change the results as a consequence of the configuration
change.
Testing the NFVI itself also presents new considerations. With a
PNF, the dedicated hardware supporting it is optimized for the
particular workload of the function. Routing hardware is specially
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built to support packet forwarding functions, while the hardware to
support a purely control-plane application (say, a DNS server, or a
Diameter function) will not have this specialized capability. In
NFV, the NFVI is required to support all types of potentially
different workload types.
Therefore, testing the NFVI requires careful consideration about what
types of metrics are sought. This, in turn, depends on the workload
type the expected VNF will be. Examples of different workload types
are data forwarding, control plane, encryption, and authentication.
All these types of expected workloads will determine the types of
metrics that should be sought. For example, if the workload is
control plane, then a metric such as jitter is not useful, but
dropped packets are critical. In a multi-tenant environment, the
NFVI could support various types of workloads. In this case, testing
with a variety of traffic types while measuring the corresponding
metrics simultaneously becomes necessary.
Test beds for any type of testing for an NFV-based system will be
largely similar to previously used test architectures. The methods
are impacted by virtualization, as described above, but the design of
test beds are similar as in the past. There are two main new
considerations:
o Since networking is based on software, which has lead to greater
automation in deployment, the test system should also be
deployable with the rest of the system in order to fully automate
the system. This is especially relevant in a DevOps environment
supported by a Continuous Integration and Continuous Deployment
(CI/CD) tool chain (see Section 4.11.3 below).
o In any performance test bed, the test system should not share the
same resources as the SUT. While multi-tenancy is a reality in
virtualization, having the test system share resources with the
SUT will impact the measured results in a performance test bed.
The test system should be deployed on a separate platform in order
not to impact the resources available to the SUT.
4.11.2. New Functionality
NFV presents a collection of new functionality in order to support
the goal of software networking. Each component on the architecture
shown in Figure 2 has an associated set of functionality that allows
VNFs to run the following: onboarding, life-cycle management for VNFs
and Network Services (NS), resource allocation, hypervisor functions,
etc.
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One of the new capabilities enabled by NFV is VNF Forwarding Graphs
(VNFFG). This refers to the graph that represents a network service
by chaining together VNFs into a forwarding path. In practice, the
forwarding path can be implemented in a variety of ways using
different networking capabilities: vSwitch, SDN, and SDN with a
northbound application. Additionally, the VNFFG might use tunneling
protocols like Virtual eXtensible Local Area Network (VXLAN). The
dynamic allocation and implementation of these networking paths will
have different performance characteristics depending on the methods
used. The path implementation mechanism becomes a variable in the
network testing of the NSs. The methodology used to test the various
mechanisms should largely remain the same; as usual, the test
environment should remain constant for each of the tests, focusing on
varying the path establishment method.
"Scaling" refers to the change in allocation of resources to a VNF or
NS. It happens dynamically at run-time, based on defined policies
and triggers. The triggers can be network, compute, or storage
based. Scaling can allocate more resources in times of need, or
reduce the amount of resources allocated when the demand is reduced.
The SUT in this case becomes much larger than the VNF itself: MANO
controls how scaling is done based on policies, and then allocates
the resources accordingly in the NFVI. Essentially, the testing of
scaling includes the entire NFV architecture components into the SUT.
4.11.3. Opportunities
Softwarization of networking functionality leads to softwarization of
the test as well. As PNFs are being transformed into VNFs, so are
the test tools. This leads to the fact that test tools are also
being controlled and executed in the same environment as the VNFs.
This presents an opportunity to include VNF-based test tools along
with the deployment of the VNFs supporting the services of the
service provider into the host data centers. Therefore, tests can be
automatically executed upon deployment in the target environment, for
each deployment, and each service. With PNFs, this was very
difficult to achieve.
This new concept helps to enable modern concepts like DevOps and
Continuous Integration and Continuous Deployment in the NFV
environment. The CI/CD pipeline supports this concept. It consists
of a series of tools, among which immediate testing is an integral
part, to deliver software from source to deployment. The ability to
deploy the test tools themselves into the production environment
stretches the CI/CD pipeline all the way to production deployment,
allowing a range of tests to be executed. The tests can be simple,
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with a goal of verifying the correct deployment and networking
establishment, but can also be more complex, like testing VNF
functionality.
5. Technology Gaps and Potential IETF Efforts
Table 1 correlates the open network virtualization research areas
identified in this document to potential IETF and IRTF groups that
could address some aspects of them. An example of a specific gap
that the group could potentially address is identified as a
parenthetical beside the group name.
+-------------------------+-----------------------------------------+
| Open Research Area | Potential IETF/IRTF Group |
+-------------------------+-----------------------------------------+
| 1) Guaranteeing QoS | IPPM WG (Measurements of NFVI) |
| | |
| 2) Performance | SFC WG, NFVRG (energy-driven |
| improvement | orchestration) |
| | |
| 3) Multiple Domains | NFVRG (multi-domain orchestration) |
| | |
| 4) Network Slicing | NVO3 WG, NETSLICES bar BoF (multi- |
| | tenancy support) |
| | |
| 5) Service Composition | SFC WG (SFC Mgmt and Config) |
| | |
| 6) End-user device | N/A |
| virtualization | |
| | |
| 7) Security | N/A |
| | |
| 8) Separation of | NFVRG (separation between transport |
| control concerns | control and services) |
| | |
| 9) Testing | NFVRG (testing of scaling) |
| | |
| 10) Function placement | NFVRG, SFC WG (VNF placement algorithms |
| | and protocols) |
+-------------------------+-----------------------------------------+
Table 1: Mapping of Open Research Areas to Potential IETF Groups
Bernardos, et al. Informational [Page 33]
RFC 8568 Network Virtualization Research Challenges April 2019
6. NFVRG Focus Areas
Table 2 correlates the currently identified NFVRG topics of interest
/ focus areas to the open network virtualization research areas
enumerated in this document. This can help the NFVRG in identifying
and prioritizing research topics. The current list of NFVRG focus
points is the following:
o Re-architecting functions, including aspects such as new
architectural and design patterns (e.g., containerization,
statelessness, serverless, control/data plane separation), SDN
integration, and proposals on programmability.
o New management frameworks, considering aspects related to new OAM
mechanisms (e.g., configuration control, hybrid descriptors) and
lightweight MANO proposals.
o Techniques to guarantee low latency, resource isolation, and other
data-plane features, including hardware acceleration, functional
offloading to data-plane elements (including NICs), and related
approaches.
o Measurement and benchmarking, addressing both internal
measurements and external applications.
+-------------------------------------+-------------------------+
| NFVRG Focus Point | Open Research Area |
+-------------------------------------+-------------------------+
| 1) Re-architecting functions | - Performance improvem. |
| | - Network Slicing |
| | - Guaranteeing QoS |
| | - Security |
| | - End-user device virt. |
| | - Separation of control |
| | |
| 2) New management frameworks | - Multiple Domains |
| | - Service Composition |
| | - End-user device virt. |
| | |
| 3) Low latency, resource isolation, | - Performance improvem. |
| etc. | - Separation of control |
| | |
| 4) Measurement and benchmarking | - Guaranteeing QoS |
| | - Testing |
+-------------------------------------+-------------------------+
Table 2: Mapping of NFVRG Focus Points to Open Research Areas
Bernardos, et al. Informational [Page 34]
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7. IANA Considerations
This document has no IANA actions.
8. Security Considerations
This is an Informational RFC that details research challenges; it
does not introduce any security threat. Research challenges and gaps
related to security and privacy have been included in Section 4.8.
9. Informative References
[COMS-PS] Geng, L., Slawomir, S., Qiang, L., Matsushima, S., Galis,
A., and L. Contreras, "Problem Statement of Common
Operation and Management of Network Slicing", Work in
Progress, draft-geng-coms-problem-statement-04, March
2018.
[dynamic_chaining]
Martini, B. and F. Paganelli, "A Service-Oriented Approach
for Dynamic Chaining of Virtual Network Functions over
Multi-Provider Software-Defined Networks", Future
Internet Vol. 8, No. 2, DOI 10.3390/fi8020024, June 2016.
[dynamic_placement]
Clayman, S., Maini, E., Galis, A., Manzalini, A., and
N. Mazzocca, "The dynamic placement of virtual network
functions", 2014 IEEE Network Operations and Management
Symposium (NOMS) pp. 1-9, DOI 10.1109/NOMS.2014.6838412,
May 2014.
[etsi_gs_nfv_003]
ETSI NFV ISG, "Network Functions Virtualisation (NFV);
Terminology for Main Concepts in NFV", ETSI GS NFV 003
V1.2.1 NFV 003, December 2014,
<http://www.etsi.org/deliver/etsi_gs/
NFV/001_099/003/01.02.01_60/gs_NFV003v010201p.pdf>.
[etsi_gs_nfv_eve005]
ETSI NFV ISG, "Network Functions Virtualisation (NFV);
Ecosystem; Report on SDN Usage in NFV Architectural
Framework", ETSI GS NFV-EVE 005 V1.1.1 NFV-EVE 005,
December 2015,
<http://www.etsi.org/deliver/etsi_gs/NFV-EVE/001_099/
005/01.01.01_60/gs_NFV-EVE005v010101p.pdf>.
Bernardos, et al. Informational [Page 35]
RFC 8568 Network Virtualization Research Challenges April 2019
[etsi_gs_nfv_per_001]
ETSI NFV ISG, "Network Functions Virtualisation (NFV); NFV
Performance & Portability Best Practises", ETSI GS NFV-PER
001 V1.1.2 NFV-PER 001, December 2014,
<https://www.etsi.org/deliver/etsi_gs/nfv-per/
001_099/001/01.01.02_60/gs_nfv-per001v010102p.pdf>.
[etsi_gs_nfv_sec_001]
ETSI NFV ISG, "Network Functions Virtualisation (NFV); NFV
Security; Problem Statement", ETSI GS NFV-SEC 001 V1.1.1
NFV-SEC 001, October 2014, <http://www.etsi.org/deliver/
etsi_gs/NFV-SEC/001_099/001/01.01.01_60/
gs_NFV-SEC001v010101p.pdf>.
[etsi_nfv_whitepaper_3]
ETSI, "Network Functions Virtualisation (NFV) - White
Paper #3: Network Operator Perspectives on Industry
Progress", Issue 1, SDN & OpenFlow World
Congress Dusseldorf, Germany, October 2014,
<http://portal.etsi.org/NFV/NFV_White_Paper3.pdf>.
[google_sdn_wan]
Jain, S., et al., "B4: experience with a globally-deployed
Software Defined WAN", SIGCOMM '13: Proceedings of the ACM
SIGCOMM 2013 conference on SIGCOMM, pp. 3-14, Hong
Kong China, DOI 10.1145/2486001.2486019, August 2013.
[intel_10_differences_nfv_cloud]
Torre, P., "Discover the Top 10 Differences Between NFV
and Cloud Environments", November 2015,
<https://software.intel.com/en-us/videos/discover-the-top-
10-differences-between-nfv-and-cloud-environments>.
[itu-t-y.3300]
ITU-T, "Y.3300: Framework of software-defined networking",
ITU-T Recommendation Y.3300, June 2014,
<http://www.itu.int/rec/T-REC-Y.3300-201406-I/en>.
[itu-t-y.3301]
ITU-T, "Y.3301: Functional requirements of software-
defined networking", ITU-T Recommendation Y.3301,
September 2016,
<http://www.itu.int/rec/T-REC-Y.3301-201609-I/en>.
Bernardos, et al. Informational [Page 36]
RFC 8568 Network Virtualization Research Challenges April 2019
[itu-t-y.3302]
ITU-T, "Y.3302: Functional architecture of software-
defined networking", ITU-T Recommendation Y.3302, January
2017, <http://www.itu.int/rec/T-REC-Y.3302-201701-I/en>.
[LAYERED-SDN]
Contreras, L., Bernardos, C., Lopez, D., Boucadair, M.,
and P. Iovanna, "Cooperating Layered Architecture for
Software Defined Networking (CLAS)", Work in Progress,
draft-contreras-layered-sdn-03, November 2018.
[LIGHT-NFV]
Sriram, N., Krishnan, R., Ghanwani, A., Krishnaswamy, D.,
Willis, P., Chaudhary, A., and F. Huici, "An Analysis of
Lightweight Virtualization Technologies for NFV", Work in
Progress, draft-natarajan-nfvrg-containers-for-nfv-03,
July 2016.
[multi-domain_5GEx]
Bernardos, C., Gero, B., Di Girolamo, M., Kern, A.,
Martini, B., and I. Vaishnavi, "5GEx: Realizing a Europe-
wide Multi-domain framework for software-defined
infrastructures", Transactions on Emerging
Telecommunications Technologies Vol. 27, No. 9,
pp. 1271-1280, DOI 10.1002/ett.3085, July 2016.
[MULTI-NMRG]
Bernardos, C., Contreras, L., Vaishnavi, I., Szabo, R.,
Li, X., Paolucci, F., Sgambelluri, A., Martini, B.,
Valcarenghi, L., Landi, G., Andrushko, D., and A. Mourad,
"Multi-domain Network Virtualization", Work in Progress,
draft-bernardos-nmrg-multidomain-00, March 2019.
[NETSLICES]
Galis, A., Dong, J., Makhijani, K., Bryant, S., Boucadair,
M., and P. Martinez-Julia, "Network Slicing - Introductory
Document and Revised Problem Statement", Work in
Progress, draft-gdmb-netslices-intro-and-ps-02, February
2017.
[NFV-COTS] Mo, L. and B. Khasnabish, "NFV Reliability using COTS
Hardware", Work in Progress, draft-mlk-nfvrg-nfv-
reliability-using-cots-01, October 2015.
Bernardos, et al. Informational [Page 37]
RFC 8568 Network Virtualization Research Challenges April 2019
[nfv_piecing]
Luizelli, M., Bays, L., Buriol, L., Barcellos, M., and
L. Gaspary, "Piecing together the NFV provisioning puzzle:
Efficient placement and chaining of virtual network
functions", 2015 IFIP/IEEE International Symposium on
Integrated Network Management (IM) pp. 98-106,
DOI 10.1109/INM.2015.7140281, May 2015.
[nfv_sota_research_challenges]
Mijumbi, R., Serrat, J., Gorricho, J-L., Bouten, N.,
De Turck, F., and R. Boutaba, "Network Function
Virtualization: State-of-the-art and Research Challenges",
IEEE Communications Surveys & Tutorials Volume: 18,
Issue: 1, pp. 236-262, DOI 10.1109/COMST.2015.2477041,
September 2015.
[NFVRG-TOPO]
Bagnulo, M. and D. Dolson, "NFVI PoP Network Topology:
Problem Statement", Work in Progress, draft-bagnulo-nfvrg-
topology-01, March 2016.
[ngmn_5G_whitepaper]
NGMN Alliance, "NGMN 5G White Paper", Version 1.0,
February 2015,
<https://www.ngmn.org/fileadmin/ngmn/content/
images/news/ngmn_news/NGMN_5G_White_Paper_V1_0.pdf>.
[omniran] IEEE, "Recommended Practice for Network Reference Model
and Functional Description of IEEE 802 Access Network",
P802.1CF IEEE Draft, December 2017.
[onf_tr_521]
Open Networking Foundation, "SDN Architecture", ONF
TR-521 TR-521, Issue 1.1, February 2016,
<https://www.opennetworking.org/images/stories/downloads/
sdn-resources/technical-reports/
TR-521_SDN_Architecture_issue_1.1.pdf>.
[OpenFlow] Open Networking Foundation, "OpenFlow Switch
Specification", ONF TS-025, Version 1.5.1 (Protocol
version 0x06), March 2015.
[openmano_dataplane]
Lopez, D., "OpenMANO: The Dataplane Ready Open Source NFV
MANO Stack", March 2015, <https://www.ietf.org/
proceedings/92/slides/slides-92-nfvrg-7.pdf>.
Bernardos, et al. Informational [Page 38]
RFC 8568 Network Virtualization Research Challenges April 2019
[RFC5810] Doria, A., Ed., Hadi Salim, J., Ed., Haas, R., Ed.,
Khosravi, H., Ed., Wang, W., Ed., Dong, L., Gopal, R., and
J. Halpern, "Forwarding and Control Element Separation
(ForCES) Protocol Specification", RFC 5810,
DOI 10.17487/RFC5810, March 2010,
<https://www.rfc-editor.org/info/rfc5810>.
[RFC6241] Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
and A. Bierman, Ed., "Network Configuration Protocol
(NETCONF)", RFC 6241, DOI 10.17487/RFC6241, June 2011,
<https://www.rfc-editor.org/info/rfc6241>.
[RFC7252] Shelby, Z., Hartke, K., and C. Bormann, "The Constrained
Application Protocol (CoAP)", RFC 7252,
DOI 10.17487/RFC7252, June 2014,
<https://www.rfc-editor.org/info/rfc7252>.
[RFC7426] Haleplidis, E., Ed., Pentikousis, K., Ed., Denazis, S.,
Hadi Salim, J., Meyer, D., and O. Koufopavlou, "Software-
Defined Networking (SDN): Layers and Architecture
Terminology", RFC 7426, DOI 10.17487/RFC7426, January
2015, <https://www.rfc-editor.org/info/rfc7426>.
[RFC7498] Quinn, P., Ed. and T. Nadeau, Ed., "Problem Statement for
Service Function Chaining", RFC 7498,
DOI 10.17487/RFC7498, April 2015,
<https://www.rfc-editor.org/info/rfc7498>.
[RFC7665] Halpern, J., Ed. and C. Pignataro, Ed., "Service Function
Chaining (SFC) Architecture", RFC 7665,
DOI 10.17487/RFC7665, October 2015,
<https://www.rfc-editor.org/info/rfc7665>.
[RFC8030] Thomson, M., Damaggio, E., and B. Raymor, Ed., "Generic
Event Delivery Using HTTP Push", RFC 8030,
DOI 10.17487/RFC8030, December 2016,
<https://www.rfc-editor.org/info/rfc8030>.
[RFC8040] Bierman, A., Bjorklund, M., and K. Watsen, "RESTCONF
Protocol", RFC 8040, DOI 10.17487/RFC8040, January 2017,
<https://www.rfc-editor.org/info/rfc8040>.
[RFC8172] Morton, A., "Considerations for Benchmarking Virtual
Network Functions and Their Infrastructure", RFC 8172,
DOI 10.17487/RFC8172, July 2017,
<https://www.rfc-editor.org/info/rfc8172>.
Bernardos, et al. Informational [Page 39]
RFC 8568 Network Virtualization Research Challenges April 2019
[SDN-AAA] Lopez, R. and G. Lopez-Millan, "Software-Defined
Networking (SDN)-based AAA Infrastructures Management",
Work in Progress, draft-marin-sdnrg-sdn-aaa-mng-00,
November 2015.
[sfc_challenges]
Medhat, A., Taleb, T., Elmangoush, A., Carella, G.,
Covaci, S., and T. Magedanz, "Service Function Chaining in
Next Generation Networks: State of the Art and Research
Challenges", IEEE Communications Magazine vol. 55, no. 2,
pp. 216-223, DOI 10.1109/MCOM.2016.1600219RP, February
2017.
[SLICE-3GPP]
Foy, X. and A. Rahman, "Network Slicing - 3GPP Use Case",
Work in Prgoress, draft-defoy-netslices-3gpp-network-
slicing-02, October 2017.
[virtualization_mobile_device]
Sproule, W. and A. Fernando, "Virtualization of Mobile
Device User Experience", US Patent 9.542.062 B2, filed
October 2013 and issued December 2014, Current
Assignee: Microsoft Technology Licensing LLC.
[vnf-p] Moens, H. and , "VNF-P: A model for efficient placement of
virtualized network functions", 10th International
Conference on Network and Service Management (CNSM) and
Workshop pp. 418-423, DOI 10.1109/CNSM.2014.7014205,
November 2014.
[VNF-VBAAS]
Rosa, R., Rothenberg, C., and R. Szabo, "VNF Benchmark-as-
a-Service", Work in Progress, draft-rorosz-nfvrg-vbaas-00,
October 2015.
[vnf_benchmarking]
Rosa, R., Rothenberg, C., and R. Szabo, "A VNF Testing
Framework Design, Implementation and Partial Results",
NFVRG IETF 97, November 2016,
<https://www.ietf.org/proceedings/97/slides/
slides-97-nfvrg-06-vnf-benchmarking-00.pdf>.
Bernardos, et al. Informational [Page 40]
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Acknowledgments
The authors want to thank Dirk von Hugo, Rafa Marin, Diego Lopez,
Ramki Krishnan, Kostas Pentikousis, Rana Pratap Sircar, Alfred
Morton, Nicolas Kuhn, Saumya Dikshit, Fabio Giust, Evangelos
Haleplidis, Angeles Vazquez-Castro, Barbara Martini, Jose Saldana,
and Gino Carrozzo for their very useful reviews and comments to the
document. Special thanks to Pedro Martinez-Julia, who provided text
for the network slicing section.
The authors want to also thank Dave Oran and Michael Welzl for their
very detailed IRSG reviews.
The work of Carlos J. Bernardos and Luis M. Contreras is partially
supported by the H2020 5GEx (Grant Agreement no. 671636) and
5G-TRANSFORMER (Grant Agreement no. 761536) projects.
Authors' Addresses
Carlos J. Bernardos
Universidad Carlos III de Madrid
Av. Universidad, 30
Leganes, Madrid 28911
Spain
Phone: +34 91624 6236
Email: cjbc@it.uc3m.es
URI: http://www.it.uc3m.es/cjbc/
Akbar Rahman
InterDigital Communications, LLC
1000 Sherbrooke Street West, 10th floor
Montreal, Quebec H3A 3G4
Canada
Email: Akbar.Rahman@InterDigital.com
URI: http://www.InterDigital.com/
Juan Carlos Zuniga
SIGFOX
425 rue Jean Rostand
Labege 31670
France
Email: j.c.zuniga@ieee.org
URI: http://www.sigfox.com/
Bernardos, et al. Informational [Page 41]
RFC 8568 Network Virtualization Research Challenges April 2019
Luis M. Contreras
Telefonica I+D
Ronda de la Comunicacion, S/N
Madrid 28050
Spain
Email: luismiguel.contrerasmurillo@telefonica.com
Pedro Aranda
Universidad Carlos III de Madrid
Av. Universidad, 30
Leganes, Madrid 28911
Spain
Email: pedroandres.aranda@uc3m.es
Pierre Lynch
Keysight Technologies
800 Perimeter Park Dr, Suite A
Morrisville, NC 27560
United States of America
Email: pierre.lynch@keysight.com
URI: http://www.keysight.com
Bernardos, et al. Informational [Page 42]