Benchmarking Methodology Working Group LM. Contreras
Internet-Draft J. Rodriguez
Intended status: Experimental L. Luque
Expires: May 6, 2021 Telefonica
November 2, 2020
5G transport network benchmarking
draft-contreras-bmwg-5g-02
Abstract
New 5G services are starting to be deployed in operational networks,
leveraging in a number of novel technologies and architectural
concepts. The purpose of this document is to overview the
implications of 5G services in transport networks and to provide
guidance on bechmarking of the infratructures supporting those
services.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Conventions used in this document . . . . . . . . . . . . . . 3
3. 5G services . . . . . . . . . . . . . . . . . . . . . . . . . 3
4. Benchmarking aspects of transport networks in 5G . . . . . . 4
5. Key Performance Indicators . . . . . . . . . . . . . . . . . 4
5.1. Control and management plane KPIs KPIs . . . . . . . . . 4
5.2. Data plane KPIs . . . . . . . . . . . . . . . . . . . . . 5
6. Guidance on 5G transport benchmarking . . . . . . . . . . . . 5
6.1. Benchmarking topology . . . . . . . . . . . . . . . . . . 5
6.2. IETF network slices . . . . . . . . . . . . . . . . . . . 6
7. Security Considerations . . . . . . . . . . . . . . . . . . . 7
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 7
9. References . . . . . . . . . . . . . . . . . . . . . . . . . 7
9.1. Normative References . . . . . . . . . . . . . . . . . . 7
9.2. Informative References . . . . . . . . . . . . . . . . . 7
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 8
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 9
1. Introduction
5G services are starting to be introduced in real operational
networks. The challenges of 5G are multiple, impacting in different
technological areas such as radio access, mobile core and transport
network. Refer to [TMV] for a general overview of different aspects
impacting 5G technology performance. From all those technological
areas, the transport network is the focus of this document.
It is important for operators to have a good basis of benchmarking
solutions, technologies and architectures before moving them into
production. With such aim, this document intends to overview
available guidelines to assist on the benchmarking of 5G transport
networks, identifying gaps that could require further work and
details.
As result, it is expected to provide guidance on benchmarking of 5G
transport network infrastructures ready for experimentation in lab
environments or real deployment in operational networks.
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2. Conventions used in this document
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC2119 [RFC2119].
3. 5G services
5G transport networks will need to accommodate different kind of
services with very distinct needs and requirements leveraging on the
same infrastructure. 5G services can be grouped in three main
categories, namely enhanced Mobile Broadband (eMBB), ultra-Reliable
and Low Latency Communications (URLLC), and massive Machine Type
Communications (mMTC). Each of them presents different inherent
characteristics spanning from ultra-low latency to high bandwidth and
high reliability. For instance, eMMB services are expected to
provide peak bit rates of up to 1 Gbps, uRRLC services will require
latencies as lower as below microsecond delays, and mMTC will demand
to support up to 100 times the number of current sessions. All these
features impose great constraints to the networks deployed today in
backhaul and aggregation, in terms of not only network capacity but
also in terms of data processing, especially for guaranteeing very
low latencies.
The impact in the transport network of those challenges is increased
by some other additional challenges introduced by the emergence of
two new technological paradigms: the network virtualization and the
network programmability.
In one hand, virtualization will introduce uncertainty on the traffic
patterns due to the flexibility and scalability in the deployment
traffic sources in the transport network. On the other hand,
programmability will potentially enable automated reconfiguration of
the transport network which requires coordination mechanisms to avoid
misconfigurations.
A final consideration is the introduction of the network slicing
concept in 5G networks. According to that, the objective is to
provide customized and tailored logical networks to different
customers, allocating resources for the specific customer service
request. With this respect the IETF has initiated the work in
transport slicing (see
[I-D.nsdt-teas-ietf-network-slice-definition]).
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4. Benchmarking aspects of transport networks in 5G
The benchmarking aspects of 5G transport networks can be then
structured in the following manner:
Data plane benchmarking: aspects to consider in data plane
benchmarking refer to both hardware capabilities as well as to
transport encapsulations. Examples of hardware capabilities are
recent developments such as IEEE TSN, and example of encapsulation
is SRv6 [I-D.ietf-spring-srv6-network-programming].
Control plane benchmarking: aspects to consider for control plane
relates to transport infrastructure programmability. In this case
some previous works exists such as RFC8456 [RFC8456].
Management plane benchmarking: one specific aspect of management
benchmarking in 5G refers to the capability of managing the
transport network slice lifecycle.
Architecture benchmarking: new architectural frameworks are being
conceived to support advanced services like 5G. An example of
these architectures is [I-D.ietf-detnet-architecture].
5. Key Performance Indicators
In order to define benchmarking criteria it is convenient to
formalize Key Performance Indicators (KPIs) to assist on the
assessment of the performance of the technologies under analysis.
5.1. Control and management plane KPIs KPIs
[I-D.nsdt-teas-ietf-network-slice-definition] introduces the concept
of IETF Network Slice controller (NSC) as the element in charge of
realizing, maintaining and monitor the IETF Network Slices as
requested by higher level systems. The element itself can be
assimilated to any other controller. From that perspective, it is
possible to leverage on RFC8456 [RFC8456] to identify suitable KPIs.
Thus, the following KPIs can be considered:
o Performance KPIs, including asynchronous message processing time
and rate, proactive and reactive IETF network slice provisioning
time, etc.
o Scalability KPIs, such as control sessions capacity, number of
IETF network slices handled, etc.
o Security KPIs, like exception handling, denial-of-service attacks,
etc.
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o Reliability KPIs, as failover time for the NSC.
Apart from that, other KPIs related to the monitoring and maintenance
of the IETF network slices can be considered, as the ones related to
telemetry.
5.2. Data plane KPIs
Data Plane KPIs will help to predict data plane performance under
different measurement conditions. Existing metrics to consider are:
o Bandwidth, considered as the maximum achievable throughput between
two points. Those points can represent the ingress and egress
ports of a equipment (e.g., to determine maximum throughput ofg a
single element) or to an end-to-end setup. The througput could be
differentieted in both directions of the link (i.e., upling and
downlink).
o Latency, considered as the network delay when transmitting between
source and destination endpoints. This can apply to a single box
(e.g., delay induced by a router implementing certain technology)
or to a network scenario defined by a certain topology. RFC2681
[RFC2681] and RFC7679 [RFC7679] discuss about two-way (i.e., round
trip time) and one-way delay metrics, respectively.
o Jitter, understood as jitter the observable packet delay variation
(PDV) as defined by RFC3393 [RFC3393], which is measured by the
difference in the one-way.
o Other general data-plane related issues affected for the usage of
specific data plane technologies and/or encapsulations, such as
MTU size, etc.
o Other data-plane related issues specific to 5G such as e.g. the
capability of isolation, understood as the avoidance of
interference (i.e., affection) of traffic from different users in
case of one of those user misbehaves or consumes more resources
than expected.
6. Guidance on 5G transport benchmarking
To be completed.
6.1. Benchmarking topology
5G networks can be as complex as the one in Figure 1, from
[I-D.rokui-5g-ietf-network-slice]. It comprises of fronthaul,
midhaul, backhaul and even backbone segments, spanning end-to-end.
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Each of those segments will have particularities, in terms of
technologies used or routing solutions in place. In addition to
that, because of the specific needs of the traffic to be supported,
there will be different requirements applying to each of those
segments. A clear example is the fronthaul segment, where protocols
like CPRI or eCPRI will impose strict latency and bandwidth
requirements, for instance.
<--------------------- 5G E2E Network Slice --------------------->
<-------------- RS ---------------> <- CS ->
<--- INS_3 ---> <-- INS_4 --> <-- INS_1 --> <--- INS_2 --->
......................................
: RAN :
: ...... ...... : ........ ......
:|----| : : |----| : : |----| : : : |------| : : |-----|
:| RU | : FN : | DU | : MN : | CU | : : TN1 : | Core | :TN2 : | App |
:|----| : : |----| : : |----| : : : |------| : : |-----|
: :....: :....: : :......: :....:
: :
:....................................:
Legend
INS: 5G IETF Network Slice
RS: RAN Slice
CS: Core Slice
FN: Fronthaul network
MN: Midhaul network
TN: Transport network
DU: Distributed Unit
CU: Central Unit
RU: Radio Unit
App: Mobile Application Servers
Figure 1: Transport segments in 5G networks
Since different restrictions apply, it will be necessary to consider
specific topologies for each of thise segments, able to represent
typical but meaningful deployment scenarios
6.2. IETF network slices
On top of the network above, thanks to the network slicing approach,
it will be possible to build logical networks tailored to specific
needs and services (e.g., eMBB, uRLLC, etc). As consequence, for the
different topologies defined for the distinct transport network
segments, it can be necessary to benchmark distinct kind of IETF
network slices. The disctinction will come from the parametrization
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used, expressed in base a number of parameters and attributes as
described in [I-D.contreras-teas-slice-nbi].
An important aspect to test is the idea of isolation, or how a IETF
network slice is not affected for a misbehavior on other IETF network
slices supported by the same physical infrastructure. Different
transport technologies can have distinct behaviors in this respect.
For instance traffic policing or shaping mechanisms, hierarchical
QoS, allocation of dedicated resources as FlexE calendar slots, etc.
In this respect a common scenario can be solved follwoing different
strategis according to the capabilities of each transport technology
in place.
7. Security Considerations
This draft does not include any security considerations.
8. IANA Considerations
This draft does not include any IANA considerations
9. References
9.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/info/rfc2119>.
9.2. Informative References
[I-D.contreras-teas-slice-nbi]
Contreras, L., Homma, S., and J. Ordonez-Lucena, "IETF
Network Slice use cases and attributes for Northbound
Interface of controller", draft-contreras-teas-slice-
nbi-03 (work in progress), October 2020.
[I-D.ietf-detnet-architecture]
Finn, N., Thubert, P., Varga, B., and J. Farkas,
"Deterministic Networking Architecture", draft-ietf-
detnet-architecture-13 (work in progress), May 2019.
[I-D.ietf-spring-srv6-network-programming]
Filsfils, C., Camarillo, P., Leddy, J., Voyer, D.,
Matsushima, S., and Z. Li, "SRv6 Network Programming",
draft-ietf-spring-srv6-network-programming-24 (work in
progress), October 2020.
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[I-D.nsdt-teas-ietf-network-slice-definition]
Rokui, R., Homma, S., Makhijani, K., Contreras, L., and J.
Tantsura, "Definition of IETF Network Slices", draft-nsdt-
teas-ietf-network-slice-definition-00 (work in progress),
October 2020.
[I-D.rokui-5g-ietf-network-slice]
Rokui, R., Homma, S., Foy, X., Contreras, L., Eardley, P.,
Makhijani, K., Flinck, H., Schatzmayr, R., Tizghadam, A.,
Janz, C., and H. Yu, "IETF Network Slice for 5G and its
characteristics", draft-rokui-5g-ietf-network-slice-00
(work in progress), November 2020.
[RFC2681] Almes, G., Kalidindi, S., and M. Zekauskas, "A Round-trip
Delay Metric for IPPM", RFC 2681, DOI 10.17487/RFC2681,
September 1999, <https://www.rfc-editor.org/info/rfc2681>.
[RFC3393] Demichelis, C. and P. Chimento, "IP Packet Delay Variation
Metric for IP Performance Metrics (IPPM)", RFC 3393,
DOI 10.17487/RFC3393, November 2002,
<https://www.rfc-editor.org/info/rfc3393>.
[RFC7679] Almes, G., Kalidindi, S., Zekauskas, M., and A. Morton,
Ed., "A One-Way Delay Metric for IP Performance Metrics
(IPPM)", STD 81, RFC 7679, DOI 10.17487/RFC7679, January
2016, <https://www.rfc-editor.org/info/rfc7679>.
[RFC8456] Bhuvaneswaran, V., Basil, A., Tassinari, M., Manral, V.,
and S. Banks, "Benchmarking Methodology for Software-
Defined Networking (SDN) Controller Performance",
RFC 8456, DOI 10.17487/RFC8456, October 2018,
<https://www.rfc-editor.org/info/rfc8456>.
[TMV] "Validating 5G Technology Performance", 5G PPP TMV WG
white paper , June 2019.
Acknowledgments
This work has been partly funded by the European Commission through
the H2020 project 5G-EVE (Grant Agreement no. 815074).
Contributors
A. Florez and D. Artunedo (both from Telefonica) have also
contributed to this document from their work in 5GENESIS project.
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Authors' Addresses
Luis M. Contreras
Telefonica
Ronda de la Comunicacion, s/n
Sur-3 building, 3rd floor
Madrid 28050
Spain
Email: luismiguel.contrerasmurillo@telefonica.com
URI: http://lmcontreras.com/
Juan Rodriguez
Telefonica
Zurbaran, 12
Madrid 28010
Spain
Email: juan.rodriguezmartinez@telefonica.com
Lourdes Luque
Telefonica
Zurbaran, 12
Madrid 28010
Spain
Email: lourdes.luquecanto@telefonica.com
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