Internet DRAFT - draft-irtf-nfvrg-gaps-network-virtualization
draft-irtf-nfvrg-gaps-network-virtualization
NFVRG CJ. Bernardos
Internet-Draft UC3M
Intended status: Informational A. Rahman
Expires: March 6, 2019 InterDigital
JC. Zuniga
SIGFOX
LM. Contreras
TID
P. Aranda
UC3M
P. Lynch
Ixia
September 2, 2018
Network Virtualization Research Challenges
draft-irtf-nfvrg-gaps-network-virtualization-10
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 guaranteeing quality-of-service, performance
improvement, supporting 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 IETF/IRTF
that could address some of these challenges. This document is a
product of the Network Function Virtualization Research Group
(NFVRG).
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
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Table of Contents
1. Introduction and scope . . . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Background . . . . . . . . . . . . . . . . . . . . . . . . . 5
3.1. Network Function Virtualization . . . . . . . . . . . . . 5
3.2. Software Defined Networking . . . . . . . . . . . . . . . 7
3.3. ITU-T functional architecture of SDN . . . . . . . . . . 12
3.4. Multi-access Edge Computing . . . . . . . . . . . . . . . 13
3.5. IEEE 802.1CF (OmniRAN) . . . . . . . . . . . . . . . . . 14
3.6. Distributed Management Task Force . . . . . . . . . . . . 14
3.7. Open Source initiatives . . . . . . . . . . . . . . . . . 14
4. Network Virtualization Challenges . . . . . . . . . . . . . . 16
4.1. Introduction . . . . . . . . . . . . . . . . . . . . . . 16
4.2. Guaranteeing quality-of-service . . . . . . . . . . . . . 16
4.2.1. Virtualization Technologies . . . . . . . . . . . . . 17
4.2.2. Metrics for NFV characterization . . . . . . . . . . 17
4.2.3. Predictive analysis . . . . . . . . . . . . . . . . . 18
4.2.4. Portability . . . . . . . . . . . . . . . . . . . . . 19
4.3. Performance improvement . . . . . . . . . . . . . . . . . 19
4.3.1. Energy Efficiency . . . . . . . . . . . . . . . . . . 19
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4.3.2. Improved link usage . . . . . . . . . . . . . . . . . 20
4.4. Multiple Domains . . . . . . . . . . . . . . . . . . . . 20
4.5. 5G and Network Slicing . . . . . . . . . . . . . . . . . 21
4.5.1. Virtual Network Operators . . . . . . . . . . . . . . 22
4.5.2. Extending Virtual Networks and Systems to the
Internet of Things . . . . . . . . . . . . . . . . . 23
4.6. Service Composition . . . . . . . . . . . . . . . . . . . 24
4.7. End-user device virtualization . . . . . . . . . . . . . 25
4.8. Security and Privacy . . . . . . . . . . . . . . . . . . 26
4.9. Separation of control concerns . . . . . . . . . . . . . 27
4.10. Network Function placement . . . . . . . . . . . . . . . 28
4.11. Testing . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.11.1. Changes in methodology . . . . . . . . . . . . . . . 28
4.11.2. New functionality . . . . . . . . . . . . . . . . . 30
4.11.3. Opportunities . . . . . . . . . . . . . . . . . . . 31
5. Technology Gaps and Potential IETF Efforts . . . . . . . . . 31
6. NFVRG focus areas . . . . . . . . . . . . . . . . . . . . . . 32
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 33
8. Security Considerations . . . . . . . . . . . . . . . . . . . 33
9. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 33
10. Informative References . . . . . . . . . . . . . . . . . . . 34
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 39
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 datacenters.
Some of the network virtualization mechanisms that are being
considered include: 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.
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This document represents the consensus of the NFV Research Group. It
has been reviewed by the Research Group 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 (NVF) Industrial Study Group (ISG)
[etsi_gs_nfv_003], the 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. 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.
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 which 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) lifecycle and coordinates the management of NS
lifecycle, VNF lifecycle (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.
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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 lifecycle management of VNF.
3. Background
This section briefly describes some basic background technologies, as
well as other standards developing organizations and open source
initiatives working on network virtualization or related topics.
3.1. Network Function Virtualization
The ETSI ISG NFV is a working group which, since 2012, aims 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 framework is composed of three domains (Figure 1):
o Virtualized Network Function, running over the NFVI.
o NFV Infrastructure (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
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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.
+-------------------------------------------+ +---------------+
| 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,
and Virtualization Layer.
o Virtualized Infrastructure Manager(s) (VIM).
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o NFV Orchestrator.
o VNF Manager(s).
o Service, VNF and Infrastructure Description.
o Operations and Business Support Systems (OSS/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
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.
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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. 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.
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+----------+
| ------- |
| |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 | |
| | | +------------------------------------+ |
| | | Controller 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
(NE), which expose their capabilities toward the Controller plane via
a Southbound API. The Controller 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 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 Controller 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, Management 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 which can easily and quickly
configure and tune the network at each layer.
In RFC7426 [RFC7426], the IRTF Software-Defined Networking Research
Group (SDNRG) documented a layer model of an SDN architecture, since
this has been a controversial discussion topic: what exactly is SDN?
what is the layer structure of the SDN architecture? how do layers
interface with each other? etc.
Figure 4 reproduces the figure included in RFC7426 [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 inter-
process 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 Applications. All planes mentioned above are
connected via interfaces. Additionally, RFC7426 [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).
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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 Telecommunication standardization sector of the International
Telecommunication Union (ITU) -- the ITU-T -- has also looked into
SDN architectures, defining a slightly modified one from what other
SDOs have done. ITU-T provides in the recommendation ITU-T Y.3302
[itu-t-y.3302] 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
provides functionalities for managing the functionalities of SDN
layers, i.e., SDN-AL, SDN-CL and SDN-RL. MMF interacts with these
layers using MMFA, MMFC, and 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||
| +---+ +-------+| . |+------++----++----+|
+---------------------+ . +--------------------+
Figure 5: ITU-T SDN functional architecture
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, including also
applications from 3rd parties. These distributed computing
capabilities will make available IT infrastructure as in a cloud
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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, which 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 unifying 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
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
(CIM), for cloud infrastructure management; the Network Management
(NETMAN), for VNF management; and, the Virtualization Management
(VMAN), for virtualization infrastructure management.
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
datacenter, managed through a dashboard or via the OpenStack API.
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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 lifecycle
management.
o OpenDayLight. OpenDaylight (ODL) is a highly available, modular,
extensible and scalable multi-protocol 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 ONOS (Open Network Operating System) project is an open
source community hosted by The Linux Foundation. The goal of the
project is to create a SDN operating system for communications
service providers that is designed for scalability, high
performance and high availability.
o OpenContrail. OpenContrail is an Apache 2.0-licensed project that
is built using standards-based protocols and provides all the
necessary components for network virtualization-SDN controller,
virtual router, analytics engine, and published northbound APIs.
It has an extensive REST API to configure and gather operational
and analytics data from the system.
o OPNFV. 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 Management
(VIM) by integrating components from upstream projects such as
OpenDaylight, OpenStack, Ceph Storage, KVM, Open vSwitch, and
Linux. These components, along with application programmable
interfaces (APIs) to other NFV elements form the basic
infrastructure required for Virtualized Network Functions (VNF)
and Management and Network 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
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previous projects, such Telefonica's OpenMANO or Canonical's Juju,
among others.
o OpenBaton. OpenBaton is a ETSI NFV compliant Network Function
Virtualization Orchestrator (NFVO). OpenBaton was part of the
OpenSDNCore project started with the objective of providing a
compliant implementation of the ETSI NFV specification.
o ONAP. ONAP (Open Network Automation Platform) 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. SONA (Simplified Overlay Network Architecture) is an
extension to ONOS to have a 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 former open
source activities that relate to network virtualization research, we
can highlight: policy-based resource management, analytics for
visibility and orchestration, service verification with regards to
security and resiliency.
4. Network Virtualization Challenges
4.1. Introduction
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' core
to server farms scattered in datacenters (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 quality-of-service in an NFV environment with
virtualized and distributed computing, storage and networking
functions is more challenging than providing the equivalent in
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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]
[I-D.mlk-nfvrg-nfv-reliability-using-cots] [etsi_nvf_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 quality-of-service 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 VM and more suitable
for dealing with network functionalities.
Lately, a number of light-weight virtualization technologies
including containers, unikernels (specialized VMs) and minimalistic
distributions of general-purpose OSes have appeared as virtualization
approaches that can be used when constructing an NFV platform.
[I-D.natarajan-nfvrg-containers-for-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
measurement 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 it to highly distributed 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
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applications running over transport layer protocols (e.g., TCP, 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 drafts related to the topic of network
virtualization. In addition to using IPPM metrics to evaluate the
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 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
virtual network functions in the same way when possible, thereby
allowing direct comparison.
As stated in the document [RFC8172], there is a clear motivation for
the work on performance metrics for NFV [etsi_gs_nfv_per_001], that
is worth replicating 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 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] [I-D.rorosz-nfvrg-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
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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 trouble-makers 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 which the
VM Descriptor and Compute Host Descriptor should contain for the
appropriate deployment of VM images over an NFVI (i.e. a "telco
datacenter"), in order to guarantee high and predictable performance
of data plane workloads while assuring their portability. In
addition, the document provides a set of recommendations on the
minimum requirements which HW and hypervisor should have for a "telco
datacenter" suitable for different workloads (data-plane, control-
plane, etc.) present in VNFs. The purpose of this document 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. There are therefore 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, (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
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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 com- ponents 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 need to be considered. Aspects like the ones described
in [I-D.bagnulo-nfvrg-topology] on NFV data center topology design
have to be carefully looked at as well.
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.
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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/) [I-D.bernardos-nfvrg-multidomain]
[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 to be integrated 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 much 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 new
emerging services like tactile Internet and 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
latency), and a battery life time exceeding by a factor of thousands
that of smart phones 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 network slice from an IP infrastructure
viewpoint is currently undergoing intense debate
[I-D.geng-coms-problem-statement] [I-D.gdmb-netslices-intro-and-ps]
[I-D.defoy-netslices-3gpp-network-slicing] [ngmn_5G_whitepaper].
Network slicing is a key for introducing new actors in existing
market at 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
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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 to gain 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 require to tackle with
their dynamic operation environments.
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, Ryu) or
computing-oriented (e.g. OpenStack, OpenNebula, Eucalyptus).
Furthermore, it is also 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
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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, so different and heterogeneous systems can understand each
other without requiring to rely 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
devices like smart phones [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 to set-up 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
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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", "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 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 a
Service Function Chain (SFC) [sfc_challenges], which is called
Network Function Forwarding Graph (NF-FG) in ETSI. An SFC is
instantiated through selection of specific service function instances
on specific network nodes to form a service graph: this is 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 which can provide significant
benefits when applied in a softwarized network environment. There
are however many research challenges in this area, as 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 which may span across
multiple operators, for faster serviceability thus facilitating
accomplishing aforementioned goals of "load balancing and improve
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
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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 more 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 service
function chaining [RFC7665] that includes the necessary protocols or
protocol extensions to convey the Service Function Chain and Service
Function Path information to nodes that are involved in the
implementation of service functions and Service Function Chains, as
well as mechanisms for steering traffic through service functions.
In terms of actual work items, the SFC WG is has not yet considered
working on the management and configuration of SFC components related
to the support of Service Function Chaining. This part is of special
interest for operators and would be required in order to actually put
SFC mechanisms into operation. Similarly, redundancy and reliability
mechanisms for service function chaining 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. End-user device virtualization
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 networks 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
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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 (www.icirrus-
5gnet.eu).
4.8. Security and Privacy
Similar to any other situation 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 or higher than
the one required by the most critical application. Multiple and
continuous threat model analysis, as well as 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. It typically 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 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). NFV will thus require network
operators to evolve their operational and administrative security
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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 hardware (HW) of the network is considered 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 avoid such a security policy coordination,
this making the system more robust.
On a positive note, NFV may better defense 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 which have
physical HW which is distributed across multiple data centers will
also provide better fault isolation environments. This holds true in
particular if each data center is protected separately via firewalls,
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 [I-D.marin-sdnrg-sdn-aaa-mng].
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 PNFs (Physical Network Functions).
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.
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However, interaction between both could be expected in order to
optimize, scale or influence each other.
Clear mechanisms for such interaction are needed in order to avoid
malfunctioning or interference concerns. These ideas are considered
in [etsi_gs_nfv_eve005] and [I-D.irtf-sdnrg-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
virtual network functions is a resource allocation problem which
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][vnf-p], this still remains an open
challenges that requires more attention. Multi-domain also adds
another component of complexity to this problem that has to be
considered.
4.11. Testing
The impacts of network virtualization on testing can be divided into
3 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 Physical Network Functions (PNF), 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.
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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 which is necessary in order to run the SUTs.
Isolation of the SUT therefore 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 become the test
environment. In the case of VNFs which are 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
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.
Testing the NFVI therefore 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
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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 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 System Under Test (SUT). While multi-
tenenacy 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 to 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: onboarding, lifecycle management for VNFs and Networks
Services (NS), resource allocation, hypervisor functions, etc.
One of the new capabilities enabled by NFV is VNFFG (VNF Forwarding
Graphs). 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, SDN with a
northbound application, and the VNFFG might use tunneling protocols
like 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, and 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
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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
test as well. As Physical Network Functions (PNF) are being
transformed into VNFs, so have the test tools. This leads to the
fact that test tools are also being controlled and executed in the
same environment as the VNFs are. 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. Tests can therefore 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,
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 in
parenthetical beside the group name.
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+-------------------------+-----------------------------------------+
| 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 control | NFVRG (separation between transport |
| 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
6. NFVRG focus areas
Table 2 correlates the currently identified NFVRG topics of
interests/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
dataplane features, including hardware acceleration, functional
offloading to dataplane elements (including NICs), and related
approaches.
o Measurement and benchmarking, addressing both internal
measurements and external applications.
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+----------------------------------------+-------------------------+
| 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, etc | - Performance improvem. |
| | - Separation of control |
| 4-Measurement and benchmarking | - Guaranteeing QoS |
| | - Testing |
+----------------------------------------+-------------------------+
Table 2: Mapping of NFVRG Focus Points to Open Research Areas
7. IANA Considerations
N/A.
8. Security Considerations
This is an informational document, which therefore does not introduce
any security threat. Research challenges and gaps related to
security and privacy have been included in Section 4.8.
9. 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.
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10. Informative References
[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, June 2016.
[dynamic_placement]
Clayman, S., Maini, E., and A. Galis, "The dynamic
placement of virtual network functions", 2014 IEEE Network
Operations and Management Symposium (NOMS) pp. 1-9, 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>.
[etsi_gs_nfv_per_001]
ETSI GS NFV-PER 001 V1.1.2, "Network Functions
Virtualisation (NFV); NFV Performance & Portability Best
Practises", ETSI GS NFV-PER 001 V1.1.2 NFV-PER 001,
December 2014, <http://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 GS NFV-SEC 001 V1.1.1, "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_nvf_whitepaper_3]
"Network Functions Virtualisation (NFV). White Paper 3",
October 2014.
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[google_sdn_wan]
Sushant Jain et al., "B4: experience with a globally-
deployed Software Defined WAN", Proceedings of the ACM
SIGCOMM 2013 , August 2013.
[I-D.bagnulo-nfvrg-topology]
Bagnulo, M. and D. Dolson, "NFVI PoP Network Topology:
Problem Statement", draft-bagnulo-nfvrg-topology-01 (work
in progress), March 2016.
[I-D.bernardos-nfvrg-multidomain]
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", draft-bernardos-
nfvrg-multidomain-04 (work in progress), March 2018.
[I-D.defoy-netslices-3gpp-network-slicing]
Foy, X. and A. Rahman, "Network Slicing - 3GPP Use Case",
draft-defoy-netslices-3gpp-network-slicing-02 (work in
progress), October 2017.
[I-D.gdmb-netslices-intro-and-ps]
Galis, A., Dong, J., kiran.makhijani@huawei.com, k.,
Bryant, S., Boucadair, M., and P. Martinez-Julia, "Network
Slicing - Introductory Document and Revised Problem
Statement", draft-gdmb-netslices-intro-and-ps-02 (work in
progress), February 2017.
[I-D.geng-coms-problem-statement]
Geng, L., Slawomir, S., Qiang, L.,
kiran.makhijani@huawei.com, k., Galis, A., and L.
Contreras, "Problem Statement of Common Operation and
Management of Network Slicing", draft-geng-coms-problem-
statement-04 (work in progress), March 2018.
[I-D.irtf-sdnrg-layered-sdn]
Contreras, L., Bernardos, C., Lopez, D., Boucadair, M.,
and P. Iovanna, "Cooperating Layered Architecture for
SDN", draft-irtf-sdnrg-layered-sdn-01 (work in progress),
October 2016.
[I-D.marin-sdnrg-sdn-aaa-mng]
Lopez, R. and G. Lopez-Millan, "Software-Defined
Networking (SDN)-based AAA Infrastructures Management",
draft-marin-sdnrg-sdn-aaa-mng-00 (work in progress),
November 2015.
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[I-D.mlk-nfvrg-nfv-reliability-using-cots]
Mo, L. and B. Khasnabish, "NFV Reliability using COTS
Hardware", draft-mlk-nfvrg-nfv-reliability-using-cots-01
(work in progress), October 2015.
[I-D.natarajan-nfvrg-containers-for-nfv]
natarajan.sriram@gmail.com, n., Krishnan, R., Ghanwani,
A., Krishnaswamy, D., Willis, P., Chaudhary, A., and F.
Huici, "An Analysis of Lightweight Virtualization
Technologies for NFV", draft-natarajan-nfvrg-containers-
for-nfv-03 (work in progress), July 2016.
[I-D.rorosz-nfvrg-vbaas]
Rosa, R., Rothenberg, C., and R. Szabo, "VNF Benchmark-as-
a-Service", draft-rorosz-nfvrg-vbaas-00 (work in
progress), October 2015.
[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 (06/14), 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 (09/16),
September 2016,
<http://www.itu.int/rec/T-REC-Y.3301-201609-I/en>.
[itu-t-y.3302]
ITU-T, "Y.3302: Functional architecture of software-
defined networking", ITU-T Recommendation Y.3302 (01/17),
January 2017,
<http://www.itu.int/rec/T-REC-Y.3302-201701-I/en>.
[multi-domain_5GEx]
Bernardos, C., Geroe, 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, September 2016.
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[nfv_piecing]
Luizelli, M., Bays, L., and L. Buriol, "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, 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, September 2015.
[ngmn_5G_whitepaper]
"NGMN 5G. White Paper", February 2015.
[omniran] IEEE 802.1CF, "Recommended Practice for Network Reference
Model and Functional Description of IEEE 802 Access
Network", Draft 1.0 , December 2017.
[onf_tr_521]
ONF, "SDN Architecture, Issue 1.1", ONF TR-521 TR-521,
February 2016,
<https://www.opennetworking.org/images/stories/downloads/
sdn-resources/technical-reports/
TR-521_SDN_Architecture_issue_1.1.pdf>.
[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>.
[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>.
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[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>.
[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, February 2017.
[virtualization_mobile_device]
William D. Sproule, "Virtualization of Mobile Device User
Experience", Patent US 9.542.062 B2 , January 2017.
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[vnf-p] Moens, H. and Filip De Turck, "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, 2014.
[vnf_benchmarking]
Rosa, R., Rothenberg, C., and R. Szabo, "A VNF Testing
Framework Design, Implementation and Partial Results",
November 2016,
<https://www.ietf.org/proceedings/97/slides/
slides-97-nfvrg-06-vnf-benchmarking-00.pdf>.
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/
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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
Ixia
Email: plynch@ixiacom.com
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