Internet DRAFT - draft-ietf-detnet-scaling-requirements
draft-ietf-detnet-scaling-requirements
Deterministic Networking Working Group P. Liu
Internet-Draft China Mobile
Intended status: Informational Y. Li
Expires: 23 May 2024 Huawei
T. Eckert
Futurewei Technologies USA
Q. Xiong
ZTE Corporation
J. Ryoo
ETRI
S. Zhu
New H3C Technologies
X. Geng
Huawei
20 November 2023
Requirements for Scaling Deterministic Networks
draft-ietf-detnet-scaling-requirements-05
Abstract
Aiming at scaling deterministic networks, this document describes the
technical and operational requirements when the network has large
variation in latency among hops, great number of flows and/or
multiple domains without the same time source. Different
deterministic levels of applications co-exist and are transported in
such a network. This document also describes the corresponding
Deterministic Networking (DetNet) data plane enhancement
requirements.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
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material or to cite them other than as "work in progress."
This Internet-Draft will expire on 23 May 2024.
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Copyright Notice
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Conventions Used in This Document . . . . . . . . . . . . . . 4
3. Technical Requirements in Scaling Deterministic Networks . . 5
3.1. Tolerate Time Asynchrony . . . . . . . . . . . . . . . . 5
3.1.1. Support Asynchronous Clocks Across Domains . . . . . 5
3.1.2. Tolerate Clock Jitter & Wander within a Clock
Synchronous Domain . . . . . . . . . . . . . . . . . 6
3.1.3. Provide Mechanisms not Requiring Strict Time
Synchronization . . . . . . . . . . . . . . . . . . . 6
3.1.4. Provide Mechanisms not Requiring Synchronization . . 7
3.2. Support Large Single-hop Propagation Latency . . . . . . 7
3.3. Accommodate the Higher Link Speed . . . . . . . . . . . . 8
3.4. Be Scalable to The Large Number of Flows and Tolerate High
Utilization of Bandwidth . . . . . . . . . . . . . . . . 9
3.5. Tolerate Failures of Links or Nodes and Topology
Changes . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.6. Prevent Flow Fluctuation . . . . . . . . . . . . . . . . 11
3.7. Be Scalable to a Large Number of Hops with Complex
Topology . . . . . . . . . . . . . . . . . . . . . . . . 12
3.8. Support Multi-Mechanisms in Single Domain and
Multi-Domains . . . . . . . . . . . . . . . . . . . . . . 12
3.8.1. Support Provisioning of Multiple Mechanisms . . . . . 14
3.8.2. Support Mechanisms Switchover Crossing
Multi-domains . . . . . . . . . . . . . . . . . . . . 15
4. Data Plane Enhancement Requirements . . . . . . . . . . . . . 15
4.1. Support Aggregated Flow Identification . . . . . . . . . 16
4.2. Support Information used by Functions Ensuring
Deterministic Latency . . . . . . . . . . . . . . . . . . 16
5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 17
6. Security Considerations . . . . . . . . . . . . . . . . . . . 17
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 17
8. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 17
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9. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 17
10. Informative References . . . . . . . . . . . . . . . . . . . 18
Appendix A. Examples of Scaling Deterministic Network Trials . . 21
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 22
1. Introduction
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) [IEEE802.1TSN] 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 [RFC8655],
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 [RFC8938], 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.
When deterministic networks become large and/or multiple domains
should be stitched, DetNet solutions need to take into consideration
one or more of the following points:
* There is relaxed clock synchronization or no clock synchronization
in different domains. (Section 3.1)
* The end to end path is a combination of low and high latency hops.
(Section 3.2)
* There are various transmission rates supported at different ports
and on different network nodes.(Section 3.3)
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* There are a large number of flows which may be difficult to
identifiy per-flow state and cause the high utilization of
bandwidth.(Section 3.4)
* The topology change and failures of link might be more
common.(Section 3.5)
* The flow fluctuation caused by large number of flows may happen
frequently.(Section 3.6)
* The Number of Hops might be large with Complex
Topology.(Section 3.7)
* The mechanisms used to ensure bounded latency (e.g. queuing
mechanism) may be multiple or have different configuration/parameters
in multi-domains.(Section 3.8)
Such domains are normally within a single administrative control
network or multiple cooperating administrative networks within a
closed group of administrative control [RFC8655]. 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 scaling deterministic networks.
Based on the consideration above, this document describes
requirements for scaling deterministic networks which demands the
enhancement based on the existing bounded latency mechanisms and the
corresponding data plane to ensure the DetNet service for a 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.
2. Conventions Used in This Document
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 [RFC2119][RFC8174] when, and only when, they appear in all
capitals, as shown here.
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While [RFC2119] and [RFC8174] 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 scaling deterministic networks.
3. Technical Requirements in Scaling Deterministic Networks
Due to the attributes described in Introduction Section, the
corresponding technical requirements should be considered.
3.1. Tolerate Time Asynchrony
A deterministic 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.
3.1.1. Support Asynchronous Clocks Across 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[IEEE802.1Qbv][IEEE802.1Qch][IEEE802.1Qav]. 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 deterministic network MUST be prepared to
cross multiple domains (For instance, coping 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 [IEEE802.1Qdv], or using some timing compensation
mechanism. This document does not intend to list all the potential
ways.
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+--------------+ +--------------+
| | DetNet Connection | |
| TSN Domain I +-----------------------------+ TSN Domain II|
| | | |
+--------------+ +--------------+
| | | | |
Clock of TSN +--------+--------+--------+--------+
Domain I =
=
= | | | | |
Clock of TSN = +--------+--------+--------+--------+
Domain II = =
=<==D==>=
= =
Figure 1: Clock asynchrony between two TSN islands
3.1.2. Tolerate Clock Jitter & Wander within a Clock Synchronous Domain
Within a single time synchronization domain, different clock accuracy
is expected, for example the crystal oscillator in Ethernet is
specified at 100 ppm [Fast-Ethernet-MII-clock], Synchronous Ethernet
(SyncE) can achieve 50 ppb [G.8262], and more precise time
synchronization [G.8273] is expected in 5G mobile backhaul. The
clocks experience different jitter and wander. It may cause
different level of asymmetry of the path. The deterministic networks
SHOULD be able to recover or absorb such time variance within a
domain.
3.1.3. Provide Mechanisms not Requiring Strict Time Synchronization
It is usually hard to achieve the full time
synchronization(Section 3.1.1 and Section 3.1.2 ) when the scale of
networks become large and considering the size of the network
topology. Some networks like mobile backhaul use frequency
synchronization, such as SyncE, instead of the strict time
synchronization. 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.
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3.1.4. Provide Mechanisms not Requiring Synchronization
There can be a large number of traffic flows in a deterministic
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.[IEEE802.1Qcr] 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
[I-D.eckert-detnet-bounded-latency-problems]. When it is in use, the
requirement in Section 4.3 SHOULD be carefully met.
3.2. Support Large Single-hop Propagation Latency
In some deterministic networks, 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 requirement for propagation
delays in end-to-end computations is needed, 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 delay on cycle based methods, but not to specify any
solution. For a cyclic based method, suppose a deterministic 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 more than 20 us. In [IEEE802.1Qch], propagation
delay is part of the dead time imposed in a cycle, which impacts the
bandwidth utilization. However, since packet's arrival time varies
within the receiving cycle, larger cycle length means larger delay
variance.
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Upstream Node X |sending cycle | |
+--"------------+------------+
= "\ = =
= " \ = =
= " \ = =
= " \ = =
= " V = =
Downstream Node Y |receiving cycle| |
+--"----"-------+----\-------+
= " " = \ =
= " " = V resent out
= " " = =
Time Line -=--"----"-------=------------=----->
(in us) 0 | | 10 20
v v
Transmission Latency
Figure 2: The influence of transmission latency on a cyclic method
Note that Figure 2 is just to show an example of latency caused by
large single-hop propagation. CQF is not limited to 2 queues,
instead using more than 2 queues can be an option to solve large link
latency related concerns. [Multiple-CQF]describes this problem in
more detail and also proposes a mechanism to address it.
3.3. Accommodate the Higher Link Speed
A deterministic network can use higher speed links, especially for
its backbone. At the time of publication, 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
deterministic 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
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[IEEE802.1Qcr] 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.
3.4. Be Scalable to The Large Number of Flows and Tolerate High
Utilization of Bandwidth
The deterministic network may have the large number of traffic flows.
According to [RFC2475], per-flow state identification in the network
becomes infeasible as flow count scales up. So, it is almost
impossible to identify individual IP flows at the DetNet data plane
for a massive number of flows, neither for the per-node state machine
configuration. DetNet allows the leverage of the flow aggregation,
while individual flows may join and exit the aggregated flow rapidly
in the scaling network with large number of flows, 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.
For scaling network, proper provision at the control plane to
accommodate such higher aggregation is required. Provisioning on the
aggregated flows normally improve the scalability at the cost of
coarse granularity of the incoming traffic filtering and protection.
It is desirable that adding a flow to the network does not affect the
latency of the existing flows, or requires the complex re-
calculation, it should require as less work as possible. For
instance, only the filtering and policing configuration on the
ingress node but not the intermediate nodes. The [IEEE802.1Qbv] uses
traffic class to divide the flows and the number of it is usually 8,
so that the forwarding mechanisms itself isn't complex with a large
number of flows or higher aggregation. However, when adding new
flows, the Gate Control List may be changed, and the re-calculation
is complex. There might be the method to simplify the calculation or
configuration, which need more work to enhance it.
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Meanwhile, the traffic that requires deterministic networking can
significantly fill up the capacity of a link or the portion of the
link which is dedicated to such traffic, for example, more than 75%
and/or up to near 100% utilization. Usually, the resources required
for DetNet are reserved, however, the over-provisioning of link
capacity may not work in such cases. in order to guarantee
deterministic latency and jitter in this environment, it is better to
provide scalable queuing solutions to improve the bandwidth
utilization based on the current methods, inlcuding the TSN standard
and other published standard. For instance, when the bandwithd
utilization is high, the guard band in each cycle in [IEEE802.1Qch]
is a type of over-provisioning and can be improved with more scalable
queuing add-ons.
3.5. Tolerate Failures of Links or Nodes and Topology Changes
Deterministic networks may involve more network devices, and the
increase or decrease of network devices in deterministic 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. As the added delay
magnitudes involved are too large to use jitter compensation
techniques，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.
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3.6. Prevent Flow Fluctuation
More kinds of DetNet traffic flows described in Section 3.4 will
cause more dynamic joining or leaving of the flows, which will
further cause more flow fluctuation as well as more unpredictability
of the DetNet flows. Such as:
* Various and massive traffic flows of different applications in
scaling network easily cause more bursty traffic.
* There will be more aggregation nodes which receives the flows from
more upstream nodes adding the nondeterministic delay of the packet
treatment.
* The bursts of flows can be accumulated as the flows traverse, join,
and separate over hops. Once one of the nodes makes the minor error
of packet treatment, it will have the cumulative effect for the
downstream nodes.
* Loops formed in a network topology increase the maximum bursts of
flows exponentially [ANDREWS][BOUILLARD][THOMAS].
* The node and link failures are more common in a large network
(Section 3.5) which requires dynamic traffic steering to an alternate
path, it will also easily cause the flow fluctuation.
Noting that the non-DetNet flows are also massive and may have
potential impact on the scalability of the DetNet flows, for
instance, causing the high utilization of the bandwidth and
suppressing the possibility of more resource reservation and the
traffic steering of DetNet flows. However, it is assumed that there
will be the strategy in the ingress to deal with the non-DetNet flows
and prevent the real-time influence on the DetNet flows.
It is required to support bursty traffic and some methods to decrease
the micro-burst. So the pre-planned , ingress traffic conditioning,
scalable queuing, and enhanced capacity of buffer are required to
accommodate the flow fluctuation, and the time required for network
reconfiguration to reflect such changes is required to be controlled,
e.g., less than a specified amount of time.
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3.7. Be Scalable to a Large Number of Hops with Complex Topology
Scaling networks often results in situations where an end-to-end flow
involves a large number of hops, e.g., 15 or more. The network
topology can also be complex, including star, ring, mesh, and their
combinations, and can possibly be hierarchical. It is required to
support networks with such various types of topologies and large hop
Counts.
Delivering DetNet Quality of Service (QoS) in large and complex
networks requires end-to-end bounds on both latency and jitter, as
discussed in section 3.1 of [RFC8655]. Achievable end-to-end latency
bounds necessarily depend on the number of hops for a flow. In the
best case, the added queuing mechanism latency for DetNet QoS is
bounded by a fixed constant per hop maximum value so that the
resulting end-to-end latency bounds are a linear function of the
number of hops in addition to the inherent forwarding latency of the
nodes involved. In contrast, it is possible to achieve fixed
constant end-to-end jitter bounds that are independent of the number
of hops. Such fixed constant jitter bounds are strongly preferable
to jitter bounds that increase with an increasing number of hops.
DetNet QoS requires resource allocation in advance (e.g., of link
bandwidth and node buffer resources), as discussed in section 3.2.1
of [RFC8655]. The complexity of resource allocation processing may
range from linear (e.g. allocating resources for each hop via a path-
based resource reservation protocol such as RSVP [RFC2205]) to
potentially exponential (e.g., if solving a complex graph
optimization problem is required). This resource allocation
complexity does not directly affect achievable end-to-end latency and
jitter bounds, but it does surface in other areas such as the amount
of computation and elapsed time required to admit a new flow to a
DetNet network without disrupting the DetNet QoS provided to already
admitted flows.
Different queuing mechanisms exhibit different properties across
achievable end-to-end jitter bounds, achievable end-to-end latency
bounds and complexity. All three of these areas are considerations
in evaluation and selection of scalable DetNet queuing mechanisms.
3.8. Support Multi-Mechanisms in Single Domain and Multi-Domains
There will be large number of flows that described in Section 3.4,
the flows may have different levels of demand for DetNet
service[RFC8578] 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
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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.
The different SLA demands need different DetNet technologies as well
as the multi-domain demand in scaling network, which results in the
requirements for the diverse queuing mechanisms. For strict
deterministic services, strict queuing 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. Moreover, as queuing mechanisms development, it is also
desirable to provide the queuing solutions with multiple levels of
deterministic capabilities and schedule the reasonable resources to
achieve the optimization of network resource utilization. Those
different queuing technologies may be used in:
* the same network which requires the some of the equipment in the
same network providing multiple queuing technologies. The operator
can select the service type/level accordingly.
* the multiple domain network which support different queuing
technologies while needs the coordination with each other.
* different network implementations intended for different
application domains individually, where there is no additional
requirements for the coordination.
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Critical latency requirements:
| <->| Industrial, tight jitter, strict latency limit
|<------->| Industrial, strict latency limit
|
|<-------------.....> non-periodic, relative loose latency requirements
|
|<-------------........................> Best effort
|
+---------------------------------------------------------->
latency
Figure 3: Different levels of application requirements
3.8.1. Support Provisioning of Multiple Mechanisms
It is required to provide diversified deterministic service for
various applications in a deterministic network and to support the
corresponding diversified mechanisms(possibly at multiple DetNet QoS
levels). For instance, 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 [IEEE802.1Qbv] and
[IEEE802.1Qcr], 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 can be
complicated in 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.
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3.8.2. Support Mechanisms Switchover Crossing Multi-domains
In deterministic networks, end-to-end service may across multiple
network domains, which may adopt a variety of different queuing
mechanisms within each domain, or may have different link speed
[Section 3.3] for the same queuing mechanism.
Both of the two cases may may generate additional end-to-end latency,
jitter and packet loss, because the different queuing mechanisms and
link speed provide different scheduling granularities or phases
between the domains. For the different queuing mechanisms
switchover, such as from time synchronous mechanism[IEEE802.1Qbv] to
asynchronous mechanism[IEEE802.1Qcr] , a collaboration mechanism
crossing multi-domains MUST be considered. For the different link
speed switchover, such as from 1Gbps to 10Gbps (or reverse), the
quantification of deterministic forwarding resources (such as time
slots) of the queuing mechanism MUST match the link speed.
It requires flexible queue stitching function for the inter-domain
devices, such as increasing the buffer of inter-domain devices to
provide enough adjustment space for the flow to cross different
queuing mechanisms, the jitter compression to reduce the coupling
between two domains’ queuing mechanisms, or the additional traffic
shaping solutions to make the traffic smooth, so that for the same
scale of service flows, they can be forwarded successfully based on
different queuing mechanisms and/or the links with different speeds
in multiple domains.
4. Data Plane Enhancement Requirements
According to [RFC8938], 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 deterministic networks. By introducing
IPv6 Extension Headers [RFC8200] and Segment Routing over IPv6
[RFC8986], 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. There might be some enhancement
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of the control plane to meet the requirements in Section 3, which is
out of scope of this document and expected to be discussed and added
in or other individual documents.
[I-D.ietf-detnet-controller-plane-framework]
4.1. Support Aggregated Flow Identification
Current IPv6 aggregated flow identification is generally based on 5
or 6 tuples, IP prefixes, or wildcards as indicated in [RFC8938].
However, in deterministic networks the number of individual flows can
be huge, and they may randomly join and leave the aggregated flow at
each hop as described in Section 5. 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 scaling 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.
4.2. Support Information used by Functions Ensuring Deterministic
Latency
According to Section 3.1, the deterministic 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.
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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 deterministic network deployment.
5. Conclusion
This document specifies the technical requirements for scaling
deterministic networks and the corresponding data plane enhancement
requirements. Some of the proposed queuing mechanisms and trials are
cited, and the authors of the document think those proposals give
reasonably sound insights to enhance the current queuing mechanisms
to meet the requirements of scaling deterministic networks.
6. Security Considerations
When DetNet flows span multiple domains and require multi domain
collaboration, security guarantee needs to be strengthened. More
considerations will be described later.
7. IANA Considerations
This section will be described later.
8. Acknowledgements
The authors would like to thank Daivd Black, Jinoo Joung, 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.
9. Contributors
The following people have substantially contributed to this document:
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Zongpeng Du
China Mobile
EMail: duzongpeng@chinamobile.com
Lei Zhou
New H3C Technologies
Email: zhou.leih@h3c.com
10. Informative References
[ANDREWS] M, A., "Instability of FIFO in the permanent sessions
model at arbitrarily small network loads. ACM Trans.
Algorithms, vol. 5, no. 3, pp. 1-29,
doi:10.1145/1541885.1541894.", July 2009.
[BOUILLARD]
Corronc, B. A. B. M. A. E. L., "Deterministic network
calculus: From theory to practical implementation. in
Networks and Telecommunications. Hoboken, NJ, USA: Wiley,
doi: 10.1002/9781119440284.", January 2018.
[Fast-Ethernet-MII-clock]
"Fast Ethernet MII clock".
[G.8262] International Telecommunication Union, "Timing
characteristics of a synchronous equipment slave clock",
ITU-T Recommendation G.8262, November 2018.
[G.8273] International Telecommunication Union, "Framework of phase
and time clocks", ITU-T Recommendation G.8273, March 2018.
[I-D.dang-queuing-with-multiple-cyclic-buffers]
Liu, B. and J. Dang, "A Queuing Mechanism with Multiple
Cyclic Buffers", Work in Progress, Internet-Draft, draft-
dang-queuing-with-multiple-cyclic-buffers-00, 22 February
2021, <https://datatracker.ietf.org/doc/html/draft-dang-
queuing-with-multiple-cyclic-buffers-00>.
[I-D.eckert-detnet-bounded-latency-problems]
Eckert, T. T. and S. Bryant, "Problems with existing
DetNet bounded latency queuing mechanisms", Work in
Progress, Internet-Draft, draft-eckert-detnet-bounded-
latency-problems-00, 12 July 2021,
<https://datatracker.ietf.org/doc/html/draft-eckert-
detnet-bounded-latency-problems-00>.
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[I-D.geng-detnet-requirements-bounded-latency]
Geng, L., Willis, P., Homma, S., and L. Qiang,
"Requirements of Layer 3 Deterministic Latency Service",
Work in Progress, Internet-Draft, draft-geng-detnet-
requirements-bounded-latency-03, 7 July 2019,
<https://datatracker.ietf.org/doc/html/draft-geng-detnet-
requirements-bounded-latency-03>.
[I-D.ietf-detnet-controller-plane-framework]
Malis, A. G., Geng, X., Chen, M., Qin, F., Varga, B., and
C. J. Bernardos, "Deterministic Networking (DetNet)
Controller Plane Framework", Work in Progress, Internet-
Draft, draft-ietf-detnet-controller-plane-framework-05, 26
September 2023, <https://datatracker.ietf.org/doc/html/
draft-ietf-detnet-controller-plane-framework-05>.
[I-D.qiang-detnet-large-scale-detnet]
Qiang, L., Geng, X., Liu, B., Eckert, T. T., Geng, L., and
G. Li, "Large-Scale Deterministic IP Network", Work in
Progress, Internet-Draft, draft-qiang-detnet-large-scale-
detnet-05, 2 September 2019,
<https://datatracker.ietf.org/doc/html/draft-qiang-detnet-
large-scale-detnet-05>.
[IEEE802.1Qav]
IEEE, "IEEE Standard for Local and metropolitan area
networks -- Virtual Bridged Local Area Networks -
Amendment 12: Forwarding and Queuing Enhancements for
Time-Sensitive Streams", IEEE 802.1Qav-2009,
DOI 10.1109/IEEESTD.2010.8684664, 5 January 2010,
<https://doi.org/10.1109/IEEESTD.2010.8684664>.
[IEEE802.1Qbv]
IEEE, "IEEE Standard for Local and metropolitan area
networks -- Bridges and Bridged Networks - Amendment 25:
Enhancements for Scheduled Traffic", IEEE 802.1Qbv-2015,
DOI 10.1109/IEEESTD.2016.8613095, 18 March 2016,
<https://doi.org/10.1109/IEEESTD.2016.8613095>.
[IEEE802.1Qch]
IEEE, "IEEE Standard for Local and metropolitan area
networks -- Bridges and Bridged Networks - Amendment 29:
Cyclic Queuing and Forwarding", IEEE 802.1Qch-2017,
DOI 10.1109/IEEESTD.2017.7961303, 28 June 2017,
<https://doi.org/10.1109/IEEESTD.2017.7961303>.
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[IEEE802.1Qcr]
IEEE, "IEEE Standard for Local and Metropolitan Area
Networks -- Bridges and Bridged Networks - Amendment 34:
Asynchronous Traffic Shaping", IEEE 802.1Qcr-2020,
DOI 10.1109/IEEESTD.2020.9253013, 6 November 2020,
<https://doi.org/10.1109/IEEESTD.2020.9253013>.
[IEEE802.1Qdv]
IEEE, "IEEE Standard for Local and metropolitan area
networks -- Enhancements to Cyclic Queuing and
Forwarding", IEEE 802.1Qdv-2023, 12 July 2023.
[IEEE802.1TSN]
IEEE Standards Association, "IEEE 802.1 Time-Sensitive
Networking Task Group",
<https://www.ieee802.org/1/pages/tsn.html>.
[Multiple-CQF]
IEEE, "Multiple Cyclic Queuing and Forwarding.
https://www.ieee802.org/1/files/public/docs2021/new-finn-
multiple-CQF-0921-v02.pdf".
[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>.
[RFC2205] Braden, R., Ed., Zhang, L., Berson, S., Herzog, S., and S.
Jamin, "Resource ReSerVation Protocol (RSVP) -- Version 1
Functional Specification", RFC 2205, DOI 10.17487/RFC2205,
September 1997, <https://www.rfc-editor.org/info/rfc2205>.
[RFC2475] Blake, S., Black, D., Carlson, M., Davies, E., Wang, Z.,
and W. Weiss, "An Architecture for Differentiated
Services", RFC 2475, DOI 10.17487/RFC2475, December 1998,
<https://www.rfc-editor.org/info/rfc2475>.
[RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
May 2017, <https://www.rfc-editor.org/info/rfc8174>.
[RFC8200] Deering, S. and R. Hinden, "Internet Protocol, Version 6
(IPv6) Specification", STD 86, RFC 8200,
DOI 10.17487/RFC8200, July 2017,
<https://www.rfc-editor.org/info/rfc8200>.
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[RFC8578] Grossman, E., Ed., "Deterministic Networking Use Cases",
RFC 8578, DOI 10.17487/RFC8578, May 2019,
<https://www.rfc-editor.org/info/rfc8578>.
[RFC8655] Finn, N., Thubert, P., Varga, B., and J. Farkas,
"Deterministic Networking Architecture", RFC 8655,
DOI 10.17487/RFC8655, October 2019,
<https://www.rfc-editor.org/info/rfc8655>.
[RFC8938] Varga, B., Ed., Farkas, J., Berger, L., Malis, A., and S.
Bryant, "Deterministic Networking (DetNet) Data Plane
Framework", RFC 8938, DOI 10.17487/RFC8938, November 2020,
<https://www.rfc-editor.org/info/rfc8938>.
[RFC8986] Filsfils, C., Ed., Camarillo, P., Ed., Leddy, J., Voyer,
D., Matsushima, S., and Z. Li, "Segment Routing over IPv6
(SRv6) Network Programming", RFC 8986,
DOI 10.17487/RFC8986, February 2021,
<https://www.rfc-editor.org/info/rfc8986>.
[THOMAS] Mifdaoui, T. L. L. B. J. A. A., "On cyclic dependencies
and regulators in time-sensitive networks. IEEE Real-Time
Syst. Symp. (RTSS), York, U.K., pp. 299-311.", December
2019.
Appendix A. Examples of Scaling Deterministic Network Trials
Some 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 . [I-D.dang-queuing-with-multiple-cyclic-buffers][I
-D.qiang-detnet-large-scale-detnet].
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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.
Authors' Addresses
Peng Liu
China Mobile
Beijing
100053
China
Email: liupengyjy@chinamobile.com
Yizhou Li
Huawei
Nanjing
210012
China
Email: liyizhou@huawei.com
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Toerless Eckert
Futurewei Technologies USA
Santa Clara, 95014
United States of America
Email: tte@cs.fau.de
Quan Xiong
ZTE Corporation
Wuhan
430223
China
Email: xiong.quan@zte.com.cn
Jeong-dong Ryoo
ETRI
Daejeon
34129
South Korea
Email: ryoo@etri.re.kr
Shiyin Zhu
New H3C Technologies
Beijing
100094
China
Email: zhushiyin@h3c.com
Xuesong Geng
Huawei
Beijing
100095
China
Email: gengxuesong@huawei.com
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