Requirements for Large-Scale
Deterministic NetworksChina MobileBeijing100053Chinaliupengyjy@chinamobile.comHuaweiNanjing210012Chinaliyizhou@huawei.comFuturewei Technologies USASanta Clara95014United States of Americatte@cs.fau.deZTE CorporationWuhan430223Chinaxiong.quan@zte.com.cnETRIDaejeon34129South Korearyoo@etri.re.krNew H3C TechnologiesBeijing100094Chinazhushiyin@h3c.comHuaweiBeijing100095Chinagengxuesong@huawei.com
Networking
Deterministic Networking Working GroupLarge-scale; Deterministic; RequirementAiming at the large-scale deterministic network with long hops, large
per-hop time variation, great number of flows and/or multiple domains
without the same time source, this document describes the technical and
operational requirements when the different deterministic levels of
applications co-exist and are transported. This document also describes
the corresponding Deterministic Networking (DetNet) data plane
enhancement requirements.Packet networks are evolving from bandwidth-guaranteed Quality of
Service (QoS) to latency-guaranteed QoS that guarantees bounded latency
and definite latency. Bounded latency and definite latency can be
further understood as in-time delivery, in which a packet arrives
without exceeding a predetermined time, and on-time delivery, in which a
packet arrives at a predetermined time, respectively. In addition,
network survivability, which typically guarantees traffic recovery
within 50 ms in the event of a network failure, is evolving to a level
that guarantees lossless recovery. In order to realize the evolution of
QoS and network survivability of these networks, Time-Sensitive
Networking (TSN) technology and Deterministic Networking (DetNet)
technology are considered to be essential.TSN is a set of standards developed by the IEEE 802.1 TSN Task Group
(TG) and specifies mechanisms and
protocols necessary to realize highly available IEEE 802.1 networks with
bounded latency to carry time-sensitive, real-time application
traffic.DetNet, of which architecture is defined in RFC 8655 , provides a capability to carry specified unicast or
multicast data flows for real-time applications with extremely low data
loss rates and bounded latency under a single administrative control or
within a closed group of administrative control. The overall framework
for DetNet data plane is provided in , and
various documents on different data plane technologies and their
interworking technologies to extend the service range of data that TSN
intends to deliver to the IP (Internet Protocol) and MPLS
(Multi-Protocol Label Switching) networks have been standardized.Since TSN and DetNet were proposed, application use cases have always
been one of the hottest topics. After years of development, TSN has been
used in several industries, and has enough public awareness of the
industry for its scope. DetNet also has done a lot of work and the
standards are mature, and people become concerned about how to meet
deterministic service demand in large-scale networks.In this document we define a large-scale DetNet network as a network
that requires DetNet solutions for typically one or more of the
following key attributes:* There is relaxed clock synchronization or no clock synchronization
in different domains.* The end to end path is a combination of short and long distance
hops.* There are various transmission rate supported at the different
ports and on different network node.* There are a large number of flows which may has different level
demands of DetNet service accrossing multi-domains.* The topology change and failures of link might be more common.* The mechanisms used to ensure bounded latency (e.g. queuing
mechanism) may be multiple or have different configuration/parameter in
multi-domains.Such domains are normally within a single administrative control
network or multiple cooperating administrative networks within a closed
group of administrative control . However they
may belong to different AS domains and be controlled by multiple peering
or cascaded controllers, and at the same time they may not have the same
time clock source. Maintaining per flow status becomes impractical in
the large scale network. Aggregation and disaggregation of flows take
place at the boundaries of Detnet domains as well as within a Detnet
domain with various rules. The flow identification and packet treatment
should take care of one or combined changes introduced by the
large-scale network.Based on the defination and characteristics above, this document
describes requirements for large-scale deterministic networks which
demands the enhancement based on the existing bounded latency mechanisms
and the corresponding data plane to ensure the detnet service for single
administrative network or multiple (cooperating) administrative
networks that defined in the detnet charter. The deterministic network
for open internet is not within current scope.The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in BCP 14
when, and only
when, they appear in all capitals, as shown here.While and describe
interpretations of these key words in terms of protocol specifications
and implementations, they are used in this document to describe
technical and operational requirements to realize large-scale
deterministic networks.Due to the attributes described in Introduction Section, the
corresponding technical requirements should be considered.The large-scale network may span over multiple networks with one or
more cooperating administrative domains. There are many types of
network nodes in the multiple domains which may introduce disparate
local time variation, which require the tolerance of time
asynchrony.A large-scale network may span over multiple networks with one or
more administrative domains. One of DetNet's objectives is to stitch
TSN islands together. All devices inside a TSN domain are time-
synchronized, and most of TSN technologies rely on precise time
synchronization . However,
different TSN islands may have different clocks which are not
synchronized as shown in Figure 2, where the time difference of two
TSN domains is D. DetNet needs to connect these two TSN domains
together and provide end-to-end deterministic latency service. The
mechanism adopted by a large-scale deterministic network MUST be
prepared to cope with non-synced TSN domains. This can be done, for
example, by putting extra buffer space at the ingress of a new
domain, increasing the dead time as a guard band, or using some
timing compensation mechanism. This document does not intend to list
all the potential ways.Within a single time synchronization domain, different clock
accuracy is expected, for example the crystal oscillator in Ethernet
is specified at 100 ppm ,
Synchronous Ethernet (SyncE) can achieve 50 ppb , and more precise time synchronization is expected in 5G mobile backhaul. The clocks
experience different jitter and wander. It may cause different level
of asymmetry of the path. The large-scale networks SHOULD be able to
recover or absorb such time variance within a domain and across
multiple domains.Some networks like mobile backhaul use frequency synchronization,
such as SyncE, instead of the strict time synchronization. It is
usually hard to achieve the full time synchronization in large-scale
networks when considering the size of the network topology. It is
desired that the same deterministic performance in term of the
bounded latency and jitter SHOULD be achieved when full time
synchronization is not available, that is to say, when only partial
synchronization (SyncE is one of the examples) is in use.There are a large number of traffic flows in a large-scale
network and some of them are acyclic. Asynchronization based methods
can meet the requirements of those traffic flows. Moreover, The
mechanisms not requiring the time and/or frequency synchronization
eliminate the hardware cost and difficulty at the network nodes.
conceptually uses per-flow based
asynchronous shaper to achieve bounded latency. The effectiveness of
the per-flow based asynchronous shaper can be proven through
mathematical analysis. It can naturally tolerate the time variance,
but it exhibits the concerns of per-flow state buffer management as
shown in . When it is in
use, the requirement in Section 4.3 SHOULD be carefully met.In a large-scale network, a single hop distance is enough to
generate large latency. The speed of optical transmission in fiber is
200 km/ ms. Thus, the propagation delay of a single hop can be in the
order of a few milliseconds. It is much greater than that of a LAN,
and introduces impacts on queuing mechanisms, such as cyclic or time
aware scheduling method. So the queuing mechanism for LAN networks
needs to be extended, such as considering the propagation latency when
setting the period in both time synchronization or frequency
synchronization based methods, or setting the extra buffer in the
asynchronization based methods, to meet the requirements of
deterministic forwarding between the network nodes.Here, we use an example to describe the influence of Large
Single-hop Propagation Latency on cycle based methods, but not to
specify any solution. For a cyclic based method, suppose a large-scale
network wants to keep using the simple cycle mapping relationship,
however the link distance between two nodes is longer. Moreover, a
downstream node may have many upstream nodes each with different link
propagation delays (e.g., 9 us, 10 us, 11 us, 15 us and 20 us). In
order to absorb the longest link propagation delay, the length of
cycle must be set to at least 20 us. However, since packet's arrival
time varies within the receiving cycle, larger cycle length means
larger delay variance.A large-scale network normally uses higher speed links, especially
for its backbone. Current deterministic mechanisms used in a local
network is usually deployed in link speed of 10 Mbps or 1 Gbps, or
possibly 10 Gbps. The data rates of 10G, 100G, 400G and even higher
are commonly used in wide area networks. With the increasing of the
data rate, the network scheduling cycle can be reduced if the same
amount of the data is required to be sent each cycle for each
application. Or more data can be sent if the network cycle time
remains the same. For the former, it requires the more precise time
control (e.g. cycle in the order of a few microseconds or sub-
microseconds) for the input stream gate and the timed output buffer.
For the latter, more buffer space is required which imposes more
complex buffer or queue management and larger memory consumption.Another aspect to consider is the aggregation of the flows. In the
large-scale network, the number of flows can be hundreds or tens of
thousands. They can be aggregated into a small number of deterministic
path or tunnels. It is practical to have a few flow- based or
aggregated-flow based status in the local network. But in higher speed
and larger scale networks, it is hardly feasible. If is in use, it requires more buffers comparing
to the other full/partial time synchronized mechanisms. Therefore, it
requires optimizations to support higher link speeds.The large-scale network may have more traffic flows, which has
different levels demand of detnet service, and access in/ leave out
the detnet more irregular. The deterministic latency forwarding
mechanisms MUST scale to networks of significant size with the massive
traffic flows.There are a large number of flows which may has different demands
of DetNet service in large-scale deterministic network. provides various use cases and their requirements
in the areas of industry, electricity, buildings, etc. Some of them
clearly specify the requirements for latency and jitter, while some
others do not for the jitter. Different types of users have different
demands, just as a network provider provides different network
services for personal business or enterprise business.One kind has critical SLA requirement, such as remote control or
cloud Programmable Logic Controller (PLC) of manufacturing and
differential protection of electricity. If these services exceed the
boundaries of latency and jitter, it will bring property losses and
security risks, so they cannot tolerate with any non-deterministic
situation and can pay more on the network service. Another kind has
relatively loose levels of SLA requirement, such as cloud gaming,
cloud VR and online meeting for "consumer" networks. The users of
these applications hope to have a better network experience, but they
can tolerate it to a certain extent. For instance, exceeding the upper
boundary of latency within a small probability is acceptable. Those
different applications expect different kind of solutions, which are
related to the cost more or less. For strict deterministic services,
strict technologies need to be used, and all network devices may need
to be upgraded. For non-strict deterministic services, it may only be
necessary to upgrade some network devices (maybe edge nodes) or share
corresponding network resources.Besides, It is almost impossible to identify individual IP flows at
the DetNet data plane because of the large overhead and resource
reservation for a massive number of flows. DetNet allows the leverage
of the flow aggregation. With the large scaling of the network, proper
provision at the control plane to accommodate such higher aggregation
is required. Individual flows may join and exit the aggregated flow
rapidly which causes the dynamic in identification of the aggregated
DetNet flow. The wildcards and value ranges used in the identification
may have to change in order to ensure the aggregated flows have
compatible deterministic characteristics.The micro-burst will happen more often due to the massive traffic
flows, so some methods to decrease it are needed. introduces a reference
method requiring a scalable buffer to adjust the speed of sending the
packets, so as to keep a uniform transmission rate, and it also
support the flow aggregation. Moreover, the edge shaping based
solution to reduce the micro-burst may also work to some extent.The large-scale network may have more network devices, and the
increase or decrease of network devices in large-scale networks is
more frequent than that in LANs. A simple use case to understand is
ultra-low-latency (public) 5G transport networks, which would require
DetNet extend to every 5G base station. For some network operators,
their networks may need to connect to ~100 K base stations (serving
multiple mobile networks operators), and this number will only
increase with 5G.One the one hand, the numerous devices may lead to more network
link failures. Path switching or re-convergence of routing will cause
high latency of packet loss and retransmission, which is usually in
seconds before the network becomes stable again. It is necessary to
support certain mechanisms to adapt to failures of links or nodes and
topology changes.One the other hand, the change of the number of devices may affect
the implementation and adjustment of deterministic network mechanism,
such as the topology discovery, queuing mechanism and packet
replication and elimination. For instance, The full disjoint paths
when implementing the Packet Replication, Elimination, and Ordering
Functions (PREOF) gives a better chance of survival when one of the
nodes or links in the path fails. At the same time, it brings the
challenges of finding paths with similar distance and/or number of
hops so that there is enough buffer space to absorb the latency
difference caused by different paths when the scale is large. So, a
method is expected to support flexible planning of multiple paths and
provide a solid foundation for the implementation of PREOF.It is required to provide diversified deterministic service for
various applications in a large-scale network and to support the
corresponding diversified queuing mechanisms (possibly at multiple
DetNet QoS levels). Different queuing mechanisms can provide
different levels of latency, jitter and other guarantees, and there
may be situations where a network device provides multiple queuing
mechanisms at the same time. For example, a network aggregation
device may use the mechanisms specified in and , and other
mechanisms to forward traffic to different paths at the same time.
By providing a variety of queuing mechanisms to meet diversified
deterministic service requirements, compared with small scale
environment, this demand is particularly prominent in large-scale
networks. For instance, there may be more than eight queues or
sub-queues to support more complicated queuing mechanisms comparing
with the eight traffic classes in TSN enabled networks.Accordingly, the configuration for multiple queuing mechanisms is
complicated in large-scale deterministic networks and MUST support
the unified or simplified scheduling and management of multiple
queuing mechanisms. For example, in the distributed scenario with no
controller, the related information of the queuing mechanisms could
be advertised among the domain , including the types and related
algorithms, queue forwarding capability with different levels of
latency and jitter guarantees , etc. In the centralized scenario,
the queuing mechanisms and other information could be reported to
the controller to build a deterministic network resource topology
pool for path calculation. In addition, for refined management of
forward resources and providing resource assurance for deterministic
forwarding when establishing/ deleting sessions, it is required to
establish unified mechanisms on quantification and measurement of
resources associated with interfaces and queues.In large-scale deterministic networks, it may across multiple
network domains and adopt a variety of different queuing mechanisms
within each domain. It is required to support the inter-domain
deterministic mechanism at the inter-domain boundary nodes such as
the priority redefinition and rescheduling of queues to achieve the
end-to-end latency, bounded jitter and packet loss ratio.Moreover, changing from one queuing mechanism to another may
generate additional end-to-end latency and/or jitter which should be
taken into consideration,because the different scheduling
granularities or phase differences between the two domains requires
flexible flow aggregation and queue stitching function. For example,
when a flow is forwarded across multiple network domains based on
different queuing mechanisms, such as a time synchronous Qbv
mechanism and an asynchronous Qcr
mechanism , a collaboration mechanism
crossing multi-domains MUST be considered, such as increasing the
buffer of inter-domain devices to provide enough adjustment space
for the flow to cross different queuing mechanisms, the expected
method of jitter compression to reduce the coupling between two
domains’ queuing mechanisms, or the additional traffic shaping
solutions to make the traffic smooth, so as to provide end-to-end
deterministic services across multiple network domains.According to , the DetNet data plane can
provide or carry two metadata in MPLS and IP data planes: Flow-ID and
sequence number. The Flow-ID could be used for identification of the
DetNet flow or aggregate flow, and the sequence number could be used for
PREOF for each DetNet flow. The Flow-ID is used by both the service and
forwarding sub-layers, but the sequence number is only used by the
service layer. Metadata can also be used for OAM indications and
instrumentation of DetNet data plane operation.Generally speaking, more data plane metadata and related processing
SHOULD be supported in the large-scale deterministic networks. By
introducing IPv6 Extension Headers and Segment
Routing over IPv6 , native IPv6 data plane
should be supported with the IPv6-sepcific enhancement. This section
lists the data plane enhancement requirements based on but not limited
to the technical requirements in Section 3, describing how to use IP
and/or MPLS, and related OAM, to support a data plane method of flow
identification and packet treatment over Layer 3.Current IPv6 aggregated flow identification is generally based on 5
or 6 tuples, IP prefixes, or wildcards as indicated in . However, in large-scale deterministic networks the
number of individual flows is huge, and they may randomly join and
leave the aggregated flow at each hop. Such behaviours lead to the
difficulty in identifying aggregated flows by relying on the prefixes
or wildcards.In addition, the deterministic services may demand different
deterministic QoS requirements according to different levels of
application requirements. The flow identification with service-level
aggregation should be supported. Flow identification is also used to
quickly push a packet to a suitable queue. In a large-scale network,
there are large amount of flows requiring deterministic latency
service and normal forwarding service. Explicit flow identification
makes it easier to quickly distinguish the DetNet flows without
requiring the longest match rule on multiple tuples in IP data plane.
Therefore, explicit aggregated flow identification SHOULD be
supported.According to Section 3.1, a large-scale network should support
synchronized or asynchronized queuing mechanisms. Different queuing
mechanisms require different information to be defined as the
DetNet-specific metadata to help the functions of ensuring
deterministic latency, including regulation, queue management.etc. For
instance, the data plane needs to support the identification of cycle
for cyclic queuing and forwarding or the latency related information
for time based queuing in order to enable the applicability of the
respective queuing and/or scheduling mechanisms in the large scale
network.When different queuing mechanisms are deployed at a network node,
metadata used for each queuing mechanism should be provided at the
same time. When multiple metadata carried in one packet, metadata
should be self-described and extensible to tolerate variable number of
metadata. Meanwhile, extra data will cause extra processing, referring
to fixed or variable length lookups, total number of read/write access
to the packet header.etc. So the data plane processing efficiency also
needs to be considered when ensuring deterministic latency, but the
specific method or solution is out of scope of this document.This document does not specify what metadata and what format to be
carried in data plane. The solution document should be specific enough
on why and how the information carried as data plane meta data works
in conjunction with the queuing or other functions and how it helps
the large scale network deployment.Sequence number is the only metadata currently defined for
redundancy feature of Detnet. MPLS data plane uses Detnet-over-MPLS
label stack to carry it. At the same time, native IPv6 data plane
should be able to carry this information too. If specific IP
encapsulation or tunnel is in use, this meta data should be defined
explicitly for that data plane.Explicit route at the control plane and/or management is required
so that the "best" path can be selected to meet the latency
requirement for DetNet flows. At the data planes, MPLS label stack can
be used for this purpose. IP data plane enhancement is required to
support the explicit path selection based on IP source routing or
SRv6.This document specifies the technical requirements when ensuring the
deterministic features in the large-scale networks, and the
corresponding data plane enhancement requirements to support the them.
Some of the proposed queuing mechanisms and trials are cited and the
authors of the document think those proposals give reasonably sound
insights to enhancement the current queuing mechanisms to meet the
deterministic requirements of the large-scale networks.There are no IANA actions required by this document.This section will be described later.The authors would like to thank Lou Berger, Bala’zs Varga, Fan
Yang, Tianran Zhou,Yaakov Stein for helpful suggestions. The authors
also would like to thank Liang Geng, Peter Willis, Shunsuke Homma and Li
Qiang for their previous works.The following people have substantially contributed to this
document:Fast Ethernet MII clockTiming characteristics of a synchronous equipment slave
clockInternational Telecommunication UnionFramework of phase and time clocksInternational Telecommunication UnionIEEE Standard for Local and metropolitan area networks --
Virtual Bridged Local Area Networks - Amendment 12: Forwarding and
Queuing Enhancements for Time-Sensitive StreamsIEEEIEEE Standard for Local and metropolitan area networks --
Bridges and Bridged Networks - Amendment 25: Enhancements for
Scheduled TrafficIEEEIEEE Standard for Local and metropolitan area networks --
Bridges and Bridged Networks - Amendment 29: Cyclic Queuing and
ForwardingIEEEIEEE Standard for Local and Metropolitan Area Networks --
Bridges and Bridged Networks - Amendment 34: Asynchronous Traffic
ShapingIEEEIEEE 802.1 Time-Sensitive Networking Task GroupIEEE Standards AssociationSome trials have been carried out to verify the concept of
large-scale deterministic networks.In order to verify the deterministic technology of large-scale
networks, a trial of Deterministic IP on China Environment for Network
Innovations (CENI), which is a network built for new network technology
trial, was deployed. A network with a distance of 3,000 km over 13 hops
was tested, and the jitter was controlled within 100us.In order to verify the remote control on Deterministic IP, which
required that the latency should be controlled within 4 ms and jitter
should be controlled within 20 us. A trial cooperated with Baosteel
spanned 600 km was deployed. Baosteel is a Chinese steel company and put
forward this demand. Both of the first and second trials are based on a
frequency synchronization solution. The mechanism details could be found
in ..In order to realize multi flows synchronization on an inter-
provincial network in an exhibition, Emergen proposed the requirement
that two flows of video and virtual reality (VR) were sent from province
A, and arrived at province B together, so people can see the
synchronization of video collected by camera and the VR model. This
requirement was proposed to facilitate the virtual industry product
deployment. Due to time and other problems, it was realized by the edge
network device for a relatively lower levels of service level agreement
(SLA).Teaming up with a smart factory operator, network operators,
equipment companies, and universities, ETRI demonstrated an ultra-low
latency, high-reliability 5G wired and wireless network-based remote
industrial Internet of Things (IIoT) service by connecting a control
center and a smart factory through three different operators' networks
at a distance of 280 km. In this trail, it was demonstrated that
real-time remote smart manufacturing service is possible by making
round-trip delay below 3 ms within a smart factory and below 10 ms
between remote 5G industrial devices. In the future, the team plans to
examine feasibility of large-scale deterministic networking by
connecting smart factories in Gyeongsan, South Korea and Oulu,
Finland.These trials show that both operators and enterprise users begin to
put forward requirements for the certainty of large-scale networks, but
the implementation technologies are not exactly the same.