Asynchronous Deterministic Networking Framework for Large-Scale Networks
draft-joung-detnet-asynch-detnet-framework-04
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| Authors | Jinoo Joung , Jeong-dong Ryoo , Taesik Cheung , Yizhou Li , Peng Liu | ||
| Last updated | 2024-03-17 | ||
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draft-joung-detnet-asynch-detnet-framework-04
DetNet Working Group J. Joung
Internet-Draft Sangmyung University
Intended status: Informational J. Ryoo
Expires: 18 September 2024 T. Cheung
ETRI
Y. Li
Huawei
P. Liu
China Mobile
17 March 2024
Asynchronous Deterministic Networking Framework for Large-Scale Networks
draft-joung-detnet-asynch-detnet-framework-04
Abstract
This document describes various solutions of Asynchronous
Deterministic Networking (ADN) for large-scale networks. The
solutions in this document do not need strict time-synchronization of
network nodes, while guaranteeing end-to-end latency or jitter. The
functional architecture and requirements for such solutions are
specified.
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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Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on 18 September 2024.
Copyright Notice
Copyright (c) 2024 IETF Trust and the persons identified as the
document authors. All rights reserved.
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This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents (https://trustee.ietf.org/
license-info) in effect on the date of publication of this document.
Please review these documents carefully, as they describe your rights
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provided without warranty as described in the Revised BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1. Terms Used in This Document . . . . . . . . . . . . . . . 5
2.2. Abbreviations . . . . . . . . . . . . . . . . . . . . . . 5
3. Conventions Used in This Document . . . . . . . . . . . . . . 5
4. Framework for Latency Guarantee . . . . . . . . . . . . . . . 5
4.1. Problem Statement . . . . . . . . . . . . . . . . . . . . 5
4.2. Asynchronous Traffic Shaping (ATS) . . . . . . . . . . . 7
4.3. Flow Aggregate Interleaved Regulators (FAIR) . . . . . . 8
4.3.1. Overview of the FAIR . . . . . . . . . . . . . . . . 8
4.3.2. The performance of the FAIR . . . . . . . . . . . . . 8
4.4. Port-based Flow Aggregate Regulators (PFAR) . . . . . . . 9
4.5. Work-conserving stateless core fair queuing (C-SCORE) . . 10
4.5.1. Framework . . . . . . . . . . . . . . . . . . . . . . 10
4.5.2. Selection of delay factor for latency guarantee . . . 12
4.5.3. Network configuration for latency guarantee . . . . . 13
4.5.4. Role of entrance node for generation and update of
FT . . . . . . . . . . . . . . . . . . . . . . . . . 13
4.5.5. Role of core node for update of FT . . . . . . . . . 14
4.5.6. Mitigation of the complexity of entrance node . . . . 14
4.5.7. Compensation of time difference between nodes . . . . 14
5. Framework for Jitter Guarantee . . . . . . . . . . . . . . . 15
5.1. Problem statement . . . . . . . . . . . . . . . . . . . . 15
5.2. Buffered network (BN) . . . . . . . . . . . . . . . . . . 16
5.3. Properties of the BN . . . . . . . . . . . . . . . . . . 18
5.4. Frequency synchronization between the source and the
buffer . . . . . . . . . . . . . . . . . . . . . . . . . 19
5.5. Omission of the timestamper . . . . . . . . . . . . . . . 19
5.6. Mitigation of the increased E2E buffered latency . . . . 19
5.7. Multi-sources single-destination flows' jitter control . 20
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 20
7. Security Considerations . . . . . . . . . . . . . . . . . . . 20
8. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 21
9. Contributor . . . . . . . . . . . . . . . . . . . . . . . . . 21
10. References . . . . . . . . . . . . . . . . . . . . . . . . . 21
10.1. Normative References . . . . . . . . . . . . . . . . . . 21
10.2. Informative References . . . . . . . . . . . . . . . . . 21
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Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 24
1. Introduction
Deterministic Networking (DetNet) provides a capability to carry
specified unicast or multicast data flows for real-time applications
with extremely low data loss rates and bounded latency within a
network domain. The architecture of DetNet is defined in RFC 8655
[RFC8655], and the overall framework for DetNet data plane is
provided in RFC 8938 [RFC8938]. Various documents on DetNet IP
(Internet Protocol) and MPLS (Multi-Protocol Label Switching) data
planes and their interworking with Time-Sensitive Networking (TSN)
have been standardized. Technical elements necessary to extend
DetNet to a large-scale network spanning multiple administrative
domains are identified in [I-D.liu-detnet-large-scale-requirements].
This document considers the problem of guaranteeing both latency
upper bounds and jitter upper bounds in large-scale networks with any
type of topology, with random dynamic input traffic. The jitter is
defined as the latency difference between two packets within a flow,
not a difference from a clock signal or from an average latency, as
is summarized in RFC 3393 [RFC3393].
In large-scale networks, the end-nodes join and leave, and a large
number of flows are dynamically generated and terminated. Achieving
satisfactory deterministic performance in such environments would be
challenging. The current Internet, which has adopted the DiffServ
architecture, has the problem of the burst accumulation and the
cyclic dependency, which is mainly due to FIFO queuing and strict
priority scheduling. Cyclic dependency is defined as a situation
wherein the graph of interference between flow paths has cycles
[THOMAS]. The existence of such cyclic dependencies makes the proof
of determinism a much more challenging issue and can lead to system
instability, that is, unbounded delays [ANDREWS][BOUILLARD]. The
Internet architecture does not have an explicit solution for the
jitter bound as well. Solving the problem of latency and jitter as a
joint optimization problem would be even more difficult.
The basic philosophy behind the framework proposed in this document
is to minimize the latency bounds first by taking advantage of the
work conserving schedulers with regulators or stateless fair queuing
schedulers, and then minimize the jitter bounds by adjusting the
packet inter-departure times to reproduce the inter-arrival times, at
the boundary of a network. We argue that this is simpler than trying
to minimize the latency and the jitter at the same time. The direct
benefit of such simplicity is its scalability.
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For the first problem of guaranteeing latency bound alone, the IEEE
asynchronous traffic shaping (ATS) [IEEE802.1Qcr], the flow-aggregate
interleaved regulators (FAIR) [FAIR][Y.3113] frameworks, the port-
based flow aggregate regulators (PFAR) [ADN], and the work-conserving
stateless core fair queuing (C-SCORE) are proposed as solutions. The
key component of the ATS and the FAIR frameworks is the interleaved
regulator (IR)), which is described in [RFC9320]. The IR has a
single queue for all flows of the same class from the same input
port. The head of the queue (HOQ) is examined if the packet is
eligible to exit the regulator. To decide whether it is eligible,
the IR is required to maintain the individual flow states. The key
component of the PFAR framework is the regulators for flow aggregates
(FA) per port per class, which regulates the FA based on the sum of
average rates and the sum of maximum bursts of the flows that belong
to the FA. The key component of the C-SCORE is the packet state that
is carried as metadata. The C-SCORE does not need to maintain flow
states at core nodes, yet it works as one of the fair queuing
schedulers, which is known to provide the best flow isolation
performance. The metadata to be carried in the packet header is
simple and can be updated during the stay in the queue or before
joining the queue.
For the second problem of guaranteeing jitter bound, it is necessary
to assume that the first problem is solved, that is, the network
guarantees latency bounds. Furthermore, the network is required to
specify the value of the latency bound for a flow. The end systems
at the network boundary, or at the source and destination nodes, then
can adjust the inter-departure times of packets, such that they are
similar to their inter-arrival times. In order to identify the
inter-arrival times at the destination node, or at the network edge
near the destination, the packets are required to specify their
arrival times, according to the clock at the source, or the network
edge near the source. The clocks are not required to be time-
synchronized with any other clocks in a network. In order to avoid a
possible error due to a clock drift between a source and a
destination, they are recommended to be frequency-synchronized.
In this document, strict time-synchronization among network nodes is
avoided. It is not easily achievable, especially over a large area
network or across multiple DetNet domains. Asynchronous solutions
described in this document can provide satisfactory latency bounds
with careful design without complex pre-computation, configuration,
and hardware support usually necessary for time synchronization.
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2. Terminology
2.1. Terms Used in This Document
2.2. Abbreviations
3. 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.
4. Framework for Latency Guarantee
4.1. Problem Statement
In Section 4, we assume there are only two classes of traffic. The
high priority traffic requires latency upper bound guarantee. All
the other traffic is considered to be the low priority traffic, and
be completely preempted by the high priority traffic. High priority
(HP) traffic is our only focus.
It is well understood that the necessary conditions for a flow to
have a bounded latency inside a network, are that;
* a flow entering a network conforms to a prescribed traffic
specification (TSpec), including the arrival rate and the maximum
burst size, and
* all the network nodes serve the flow with a service rate which are
greater than or equal to the arrival rate.
These conditions make the resource reservation and the admission
control mandatory. These two functions are considered given and out
of scope of this document.
Here, the notion of arrival and service rates represent sustainable
or average values. A short-term discrepancy between these two rates
contributes to the burst size increment, which can be accumulated as
the flow passes through the downstream nodes. This results in an
increase in the latency bound. Therefore, the value of accumulated
burst size is a critical performance metric.
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The queuing and scheduling of a flow plays a key role in deciding the
accumulated burst size. Ideally, the flows can be queued in separate
queues and the queues are scheduled according to the flow rates. In
this case a flow can be considered isolated. With practical fair
schedulers, such as the Deficit Round Robin (DRR), a isolated flow
still can be affected by the other flows as much as their maximum
packet lengths.
If we adopt a separate queue per flow at an output port, and assume
identical flows from all the input ports, then the maximum burst size
of a flow out of the port, Bout, is given as the following:
Bout < Bin + (n-1)L*r/C,
where Bout is the outgoing flow's maximum burst size, Bin is the
incoming flow's maximum burst size, n is the number of the flows, L
is the maximum packet size, r is the average rate of the flow, and C
is the link capacity. This approach was taken in the integrated
services (IntServ) framework [RFC2212].
The separate queues in the aforementioned case can be too many to be
handled in real time, especially at the core of large-scale networks.
The common practice therefore is to put all the HP flows in a single
queue, and serve them with higher priority than best effort traffic.
It is also well known that, with a resource reservation, a proper
scheduling scheme such as the strict priority (SP) scheduling can
guarantee service rates larger than the arrival rates, therefore the
latency can still be guaranteed. With such a single aggregate queue
the flows are not considered isolated, however. In this case a
flow's burst size in a node can be increased proportionally to the
sum of maximum burst sizes of the other flows in the queue. That is,
Bout < Bin + (n-1)Bin*r/C.
The second term on the right-hand side represents the amount of
increased maximum burst. It is dominated by the term (n-1)Bin, which
is the maximum total burst from the other flows.
Moreover, this increased burst affects the other flows' burst size at
the next node, and this feedforward can continue indefinitely where a
cycle is formed in a network. This phenomenon is called a cyclic
dependency of a network. It is argued that the burst accumulation
can explode into infinity, therefore the latency is no longer
guaranteed.
As such, a flow is required to be isolated to a certain level, from
the other flows' bursts, such that its burst accumulations are kept
within a necessary value. By doing so, the other flows are also
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isolated. The regulators or the fair queuing schedulers are
described as solutions in this document for such isolation. They can
decrease the accumulated burst into a desirable level and can isolate
flows from others. In case of the regulators, however, if the
regulation needs a separate queue per flow, then the scalability
would be harmed just like the ideal IntServ case. In this document
solutions with the IR or the regulations on flow aggregates are
described.
Meanwhile, the fair queuing (FQ) technique limits interference
between flows to the degree of maximum packet size. Packetized
generalized processor sharing (PGPS) and weighted fair queuing (WFQ)
are representative examples of this technique [PAREKH]. In this
technique, the key is to record the service status of the flow in
real time to provide exactly the assigned amount of service. The
worst delay at each node with FQ is proportional to the maximum
packet length divided by service rate. However, for this purpose,
the complexity of managing and recording a large amount of state
information for each flow is a problem, so it is not usually applied
in practice.
To solve this problem, the flow entrance node can create state
information for each packet, including the finish time (FT) and other
necessary information, and record it in the packet. Subsequent nodes
infer the exact states of the packet at the node based on these
records without managing flow state information. This method
provides a scalable solution that enables isolation between flows by
modifying the FT based on local and initial information as needed.
In this document the method of such stateless FQ implementation in
core nodes is described.
4.2. Asynchronous Traffic Shaping (ATS)
The first solution in this document for latency guarantee is the IEEE
TSN TG's ATS technology. Essentially it is a combined effort of the
flow aggregation per node per input/output ports pair per class, and
the interleaved regulator per flow aggregate (FA). The IR examines
the HOQ, identifies the flow the packet belongs to, and transfers the
packet only when it is eligible according to the TSpec including the
maximum burst size and arrival rate of the flow. Having the flows
regulated as their TSpecs, the flow's burst size in a node can be
increased proportionally to the sum of initial maximum burst sizes of
the other flows in the queue, denoted by B.
Bout < B + (n-1)B*r/C.
The initial maximum burst size refers to the maximum burst size
specified in TSpec.
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This solution can have only one queue per FA, but suffers from having
to maintain each individual flow state. The detailed description on
ATS can be found in [IEEE802.1Qcr].
4.3. Flow Aggregate Interleaved Regulators (FAIR)
4.3.1. Overview of the FAIR
In the FAIR framework, the network can be divided into several
aggregation domains (ADs). HP flows of the same path within an AD
are aggregated into an FA. IRs per FA are implemented at the
boundaries of the ADs. An AD can consist of arbitrary number of
nodes. The FA can be further subdivided based on the flow
requirements and characteristics. For example, only video flows of
the same path are aggregated into a single FA.
Figure 1 shows an example architecture of the FAIR framework. The
IRs at the AD boundaries suppress the burst accumulations across the
ADs with the latency upper bounds intact as they do in IEEE TSN ATS,
if the incoming flows are all properly regulated, and the AD
guarantees the FIFO property to all the packets in the FA [LEBOUDEC].
It is sufficient to put every FA into a single FIFO queue in a node,
in order to maintain the FIFO property within an AD. However, in
this case, if cycles are formed, the burst accumulations inside an AD
can be accumulated indefinitely. If the topology does not include a
cycle and the latency bound requirement is not stringent, then the
FIFO queue and the SP scheduler would be allowable. Otherwise, the
FAs are recommended to be treated with separated queues and fair-
queuing schedulers for flow isolation.
.~~. +---+ .~~, +---+ .~~.
+---+ [ ] |IR | [ ] |IR | [ ] +----+
|Src|->[ AD ]->|per|->[ AD ]-> ...|per|... ->[ AD ]->|Dest|
+---+ [ ] |FA | [ ] |FA | [ ] +----+
'~~' +---+ '~~' +---+ '~~'
Figure 1: FAIR Framework
4.3.2. The performance of the FAIR
The FAIR guarantees an end-to-end delay bound with reduced complexity
compared to the traditional flow-based approach. Numerical analysis
shows that, with a careful selection of AD size, the FAIR with DRR
schedulers yields smaller latency bounds than both the IntServ and
the ATS [FAIR].
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The ATS can be considered as a special case of the FAIR with the FIFO
schedulers, where all the ADs encompass only a single hop. The
IntServ can also be considered as an extreme case of the FAIR with
fair schedulers and queues per FA, with an AD corresponding to an
entire network; therefore, regulators are unnecessary.
4.4. Port-based Flow Aggregate Regulators (PFAR)
The IR in the ATS and the FAIR suffers from two major complex tasks;
the flow state maintenance and the HOQ lookup to determine the flow
to which the packet belongs. Both tasks involve real-time packet
processing and queue management. As the number of flows increases,
the IR operation may become burdensome as much as the per- flow
regulators. Without maintaining individual flow states, however, the
flows can be isolated to a certain level, as is described in this
section.
Let us call the set of flows sharing the same input/output ports pair
the port-based FA (PFA). The only aggregation criteria for a PFA are
the ports and the class. The port-based flow aggregate regulators
(PFAR) framework puts a regulator for each PFA in an output port
module, just before the class-based queuing/scheduling system of the
output port module. The PFAR framework sees a PFA as a single flow
with the "PFA-Tspec", {the sum of the initial maximum bursts; and the
sum of the initial arrival rates} of the flows that are the elements
of the PFA; and regulates the PFA to meet its PFA-Tspec.
If we assume identical flows in a network with ideal symmetrical
topology, then the maximum burst size of an arbitrary set of flows
within an PFA, Bout, is given as the following:
Bout < Bin + (p-1)B*r/C,
where Bin is the sum of maximum burst sizes of the flows within the
FAin, B is the sum of initial maximum burst sizes of the flows within
the FAin, and p is the number of the ports in the node.
The PFARs can be placed at the output port of a node before the
output SP scheduler. The architecture is similar to that suggested
in the IEEE ATS, except that in the ATS, the IRs are placed instead
of the PFARs.
Note that Bout is affected mostly by B; in other words, the burst
size out of a node is affected mostly by the initial maximum burst
sizes of the other PFAs from different input ports of the node. This
property makes the Bout does not increase exponentially even in the
existence of cyclic dependencies. The regulator in PFAR increases
the worst latency, as much as (Bin - B)/r, while the IR does not.
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With the PFAR, the HOQ flow identification process is unnecessary,
and only the PFAs' states, instead of individual flows' states, must
be maintained at a node. In this respect, the complexity of process
of PFAR is reduced compared to IR of the ATS or the FAIR.
In a recent study [ADN], it was also shown, through a numerical
analysis with symmetrical networks with cycles, that PFAR, when
implemented at every node, can achieve comparable latency bounds to
the IEEE ATS technique.
The ATS, the FAIR, and the PFAR frameworks maintain regulators per
FA. The FAs in these frameworks are composed of the flows sharing
the same ingress/egress ports of an AD. The ADs can encompass a
single hop or multiple hops. The regulators can be the IR or the
aggregate regulator. There can be other combinations of AD and
regulator type, which could be further investigated and compared to
the frameworks introduced in this document.
4.5. Work-conserving stateless core fair queuing (C-SCORE)
4.5.1. Framework
The generalized processor sharing (GPS) [PAREKH], the weighted fair
queuing (WFQ), the virtual clock (VC), and similar other schedulers
utilize the concept of finish time (FT) that is the service order
assigned to a packet. The packet with the minimum FT in a buffer is
served first. We will call these works collectively as the fair
queuing (FQ).
As an example of the FQ, the VC scheduler [ZHANG] defines the FT to
be
F(p) = max{F(p-1), A(p)} + L(p)/r, (1)
where (p-1) and p are consecutive packets of the flow under
observation, A(p)is the arrival time of p, L(p) is the length of p,
and r is the flow service rate. The flow index is omitted.
The key idea of the FQ is to calculate the service finish times of
packets in an imaginary ideal fluid service model and use them as the
service order in the real packet-based scheduler.
While having the excellent flow isolation property, the FQ needs to
maintain the flow state, F(p-1). For every arriving packet, the flow
it belongs to has to be identified and its previous packet's FT
should be extracted. As the packet departs, the flow state, F(p),
has to be updated as well.
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We consider a framework for constructing FTs for packets at core
nodes without flow states. In a core node, the following conditions
on FTs SHOULD be met.
C1) The 'fair distance' of consecutive packets of a flow generated
at the entrance node has to be kept in the core nodes. That is;
Fh(p) >= Fh(p-1) + L(p)/r, where Fh(p) is the F(p) at core node
h.
C2) The order of FTs and the actual service order, within a flow,
have to be kept. That is; Fh(p) > Fh(p-1) and Ch(p) > Ch(p-1),
where Ch(p) is the actual service completion time of packet p at
node h.
C3) The time lapse at each hop has to be reflected. That is; Fh(p)
>= F(h-1)(p), where F(h-1)(p) is the FT of p at the node h-1,
the upstream node of h.
In essence, (1) has to be approximated in core nodes. There can be
many possible solutions to meet these conditions. We describe a
generic framework with requirements for constructing FTs in core
nodes that meet the conditions, without flow state, in the following.
Definition: An active period for a flow is a maximal interval of time
during a node busy period, over which the FT of the most recently
arrived packet of the flow is greater than the virtual time
(equivalently the system potential). Any other period is an inactive
period for the flow.
Requirement 1: In the entrance node, it is REQUIRED to obtain the FTs
with the following equation. 0 denotes the entrance node of the flow
under observation.
F0(p) = max{F0(p-1), A0(p)}+L(p)/r.
Note that if the FTs are constructed according to the above equation,
the fair distance of consecutive packets is maintained.
Requirement 2: In a core node h, it is REQUIRED to increase the FT of
a packet by an amount, d(h-1)(p), that depends on the previous node
and the packet.
Fh(p) = F(h-1)(p) + d(h-1)(p).
Requirement 3: It is REQUIRED that dh(p) is a non-decreasing function
of p, within a flow active period.
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Requirements 1, 2, and 3 specify how to construct the FT in a
network. By these requirements Conditions C1), C2), and C3) are met.
The following requirements 4 and 5 specify how the FT is used for
scheduling.
Requirement 4: It is REQUIRED that a node provides service whenever
there is a packet.
Requirement 5: It is REQUIRED that all packets waiting for service in
a node are served in the ascending order of their FTs.
We call this framework the work conserving stateless core fair
queuing (C-SCORE), which can be compared to the existing non-work
conserving scheme [STOICA].
4.5.2. Selection of delay factor for latency guarantee
For C-SCORE to guarantee E2E latency bound, the dh(p) is RECOMMENDED
to be defined as in the following.
dh(p) = SLh. (2)
The service latency of the flow at node h, denoted by SLh, is given
as follows.
SLh = Lh/Rh + L/r, (3)
where Lh is the max packet length in the node h over all the flows
that are transmitted from the output port under observation, Rh is
the link capacity of the node h, and L is the max packet length in
the flow. The service latency was first introduced in the concept of
Latency-rate server model [STILIADIS-LRS], which can be interpreted
as the worst delay from the arrival of the first packet of a new flow
until its service completion.
Consider the worst case: Right before a new flow's first packet
arrives at a node, the transmission of another packet with length Lh
has just started. This packet takes the transmission delay of Lh/Rh.
After the transmission of the packet with Lh, the flow under
observation could take only the allocated share of the link, and the
service of the packet under observation would be completed after L/r.
Therefore, the packet has to wait, in the worst case, Lh/Rh + L/r.
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The reason to add the service latency to F(h-1)(p) to get Fh(p) is to
meet Condition C3) in a most conservative way without being too
excessive. Intuitively, when every packet's FT is updated with the
flow's own worst delay, then a packet that experienced the worst
delay gets a favor. Thus its worst delay will not get any worse,
while the delay differences among flows are reflected.
When dh(p) is decided by (2), then it can be proved that
Dh(p) <= (B-L)/r + SL0 + SL1 + ... + SLh, (4)
where Dh(p) is the latency experienced by p from the arrival at the
node 0 to the departure from node h; B, L, and r are the max burst
of, max packet length of, and allocated rate to the flow under
observation that p belongs to, respectively [KAUR].
Note that the latency bound in (4) is the same to the network where
every node has a stateful FQ scheduler, including VC. The parameters
in the latency bound are all intrinsic to the flow, except Lh/Rh.
On the other hand, dh(p) may not be a function of p, and dependent
only on the nodes. Then it could be denoted as dh. For example, dh
can be the minimum or maximum observed latency at the node h.
4.5.3. Network configuration for latency guarantee
A source requests an E2E latency bound for a flow, specifying its
arrival rate, maximum packet length, and maximum burst size. If the
E2E latency bound can be met, the network admits the flow. The
network reserves the links in the path such that the sum of allocated
service rates to the flows does not exceed the link capacity.
In the process of admission decision, the service rate allocated to a
flow can be decided according to the requested latency bound of the
flow. The detailed operational procedure for such admission and
reservation is out of scope of this document.
4.5.4. Role of entrance node for generation and update of FT
It is assumed that the packet length information is written in the
packet header. Entrance node maintains the flow state, e.g. FT of
packet (p-1) at node 0 (F0(p-1)), the maximum packet length of the
flow (L), and the service rate allocated to the flow (r). It
operates a clock to identify the arrival time of a packet. It
collects the link information such as the maximum packet length of
all the flow (L0) and link capacity (R0) to calculate the delay
factor at node 0.
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Upon receiving or generating packet p, it obtains FT of packet p at
node 0 (F0(p)), according to the VC algorithm and uses it as the
service order in the entrance node. If the queue is not empty, then
it puts p in a priority queue, in which the packets are sorted
according to their FT. It also obtains the FT of packet p at node 1
(F1(p)) before or during p is in the queue. It writes F1(p), L, and
r in the packet as metadata for use in the next node 1. Finally, it
updates the flow state information F0(p-1) to F0(p).
4.5.5. Role of core node for update of FT
A core node h collects the link information such as Lh and Rh. As in
an entrance node, Lh is a rather static value, but still can be
changed over time. Upon receiving packet p, it retrieves metadata
Fh(p), L, and r, and uses Fh(p) as the FT value of the packet. It
puts p in a priority queue. It obtains Fh+1(p) by updating Fh(p)
with adding the delay factor and updates the packet metadata Fh(p)
with Fh+1(p) before or during p is in the queue.
4.5.6. Mitigation of the complexity of entrance node
Flow states still have to be maintained in entrance nodes. When the
number of flows is large, maintaining flow states can be burdensome.
However, this burden can be mitigated as follows.
The notion of an entrance node can be understood as a various edge
device, including a source itself. FT of a packet is decided based
on the maximum of F0(p-1) and A0(p); and L(p)/r. These parameters
are flow specific. There is no need to know any other external
parameters. The arrival time of p to the network, A0(p), can be
defined as the generation time of p at the source. Then F0(p) is
determined at the packet generation time and can be recorded in the
packet. In other words, the entrance node functionality can reside
in the source itself.
Therefore, we can significantly alleviate the complexity of the
proposed framework. The framework is scalable and can be applied to
any network.
4.5.7. Compensation of time difference between nodes
We have assumed zero propagation delays between nodes so far. In
reality, there are time differences between nodes, including the
differences due to the propagation delays and due to the clock
mismatches. This time difference can be defined as the difference
between the service completion time measured at the upstream node and
the arrival time measured at the current node.
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FT does not need to be precise. It is used just to indicate the
packet service order. Therefore, if we can assume that the
propagation delay is constant and the clocks do not drift, then the
time difference is constant for all the packets in a flow. In this
case the delay factor in (2) can be modified by adding the time
difference value. The E2E latency bound in (4) increases as much as
the sum of propagation delays from node 0 to h.
The notion of an entrance node can be understood as a various edge
device, including a source itself. FT of a packet is decided based
on the maximum of F0(p-1) and A0(p); and L(p)/r. These parameters
are flow specific. There is no need to know any other external
parameters. The arrival time of p to the network, A0(p), can be
defined as the generation time of p at the source. Then F0(p) is
determined at the packet generation time and can be recorded in the
packet. In other words, the entrance node functionality can reside
in the source itself.
Therefore, we can significantly alleviate the complexity of the
proposed framework. The framework is scalable and can be applied to
any network.
Moreover, the time difference can be updated only once in a while.
By the time difference compensation, the nodes become aware of the
global clock discrepancies using a periodic quantification of the
local clock discrepancies between adjacent nodes. Link by link, this
ends up producing awareness of the discrepancies between the clocks
of all the nodes, which is then included in the computation of FTs in
core nodes. It is not synchronization in a strict sense because it
does not involve the re-alignment of the clocks, only the
quantification of their differences.
Even with the clock differences and propagation delays, the C-SCORE
framework does not need global time synchronization.
5. Framework for Jitter Guarantee
5.1. Problem statement
The problem of guaranteeing jitter bounds in arbitrarily sized
networks with any type of topology with random dynamic input traffic
is considered.
There are several possible solutions to guarantee jitter bounds in
packet networks, such as IEEE TSN's cyclic queuing and forwarding
(CQF) [IEEE802.1Qch], its asynchronous variations
[I-D.yizhou-detnet-ipv6-options-for-cqf-variant], and the latency-
based forwarding (LBF) [LBF].
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The CQF requires time-synchronization across every node in the
network including the source. It is not scalable to a large network
with significant propagation delays between the nodes. The
asynchronous CQFs are scalable, but they may not satisfy
applications' jitter requirements. This is because their jitter
bounds cannot be controlled as desired, but are only determined by
the cycle time, which should be large enough to accommodate all the
traffic to be forwarded.
The systems with slotted operations such as the CQF and its
variations turn the problem of packet scheduling into the problem of
scheduling flows to fit into slots. The difficulty of such a slot
scheduling is a significant drawback in large scale dynamic networks
with irregular traffic generations and various propagation delays.
The LBF is a framework of the forwarding action decision based on the
flow and packet status, such as the delay budget left for a packet in
a node. The LBF does not specify the actions to take according to
the status. It suggests a packet slow down or speedup by changing
the service order, by pushing packets into any desirable position of
a first out queue, as a possible action to take. In essence, by
having latency budget information of every packet, the LBF is
expected to maintain the latency and jitter within desired bounds.
The processing latency required in LBF includes times 1) to lookup
the latency budget information on every packet header, 2) to decide
the queue position of the packet, 3) to modify the queue linked list,
and 4) to update the budget information on the packet upon
transmission. This processing latency, however, can affect the
scalability especially in high speed core networks.
The ATS, the FAIR, and the PFAR utilize the regulation function to
proactively prevent the possible burst accumulation in the downstream
nodes. It is not clear whether the LBF can take such preventive
action. If so the LBF can also act as a regulator and yield a
similar latency bound.
5.2. Buffered network (BN)
The BN framework in this document for jitter bound guarantee is
composed of
* a network that guarantees latency upper bounds;
* a timestamper for packets with a clock that is not necessarily
synchronized with the other nodes, which resides in between,
including the source and the network ingress interface; and
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* a buffer that can hold the packets for a predetermined interval,
which resides in between, including the destination and the
network egress interface.
Figure 2 depicts the overall architecture of the BN framework for
jitter-bound guarantees [BN]. Only a single flow is depicted between
the source and destination in Figure 2. The arrival (an), departure
(bn), and buffer-out (cn) times of the nth packet of a flow are
denoted. The end-to-end (E2E) latency and the E2E buffered latency
are defined as (bn-an) and (cn-an), respectively.
+--------------+
+-----+an +-------------+ | Network with |bn +--------+cn +-------+
| Src |-->| Timestamper |-->| latency |-->| Buffer |-->| Dest. |
+-----+ +-------------+ | guarantee | +--------+ +-------+
+--------------+
|<--------------- E2E latency ------>|
|<--------------- E2E buffered latency ---------->|
Figure 2: Buffered Network (BN) Framework for Jitter Guarantee
The buffer supports as many as the number of the flows destined for
the destination. The destination shown in Figure 2 can be an end
station or another deterministic network. The buffer holds packets
in a flow according to predefined intervals. The decision of the
buffering intervals involves the time-stamp value within each packet.
The network in between the time-stamper and the buffer can be of
arbitrarily sized network. The input traffic can be dynamic. It is
required that the network be able to guarantee and identify the E2E
latency upper bounds of the flows. The network is also required to
let the buffer be aware of the E2E latency upper bounds of the flows
it has to process. It is recommended that the E2E latency lower
bound information is provided by the network as well. The lower
bound may be contributed from the transmission and propagation delays
within the network.
The time-stamper marks on the packets their arrival times. The time-
stamping function can use the real-time transport protocol (RTP) over
the user datagram protocol (UDP) or the transmission control protocol
(TCP). Either the source or network ingress interface can stamp the
packet. In the case where the source stamps, the timestamp value is
the packet departure time from the source, which is only a
propagation time away from the packet arrival time to the network.
The source and destination do not need to share a synchronized clock.
All we need to know is the differences between the time stamps, that
is, the information about the inter-arrival times.
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5.3. Properties of the BN
Let the arrival time of the nth packet of a flow be an. Similarly,
let bn be the departure time from the network of the nth packet.
Then, a1 and b1 are the arrival and departure times of the first
packet of the flow, respectively. The first packet of a flow is
defined as the first packet generated by the source, among all the
packets that belong to the flow. Further, let cn be the buffer-out
time of the nth packet of the flow. Let us define m as the jitter
control parameter, which will be described later in detail.
Since buffers can be without cut-through capability, the processing
delay within a buffer has to be taken in account. Let gn be the
processing delay within the buffer of the nth packet of the flow.
The gn includes the time to look up the timestamp and to store/
forward the packet. However, it does not include an intentional
buffer-holding interval. By definition, cn - bn >= gn. Let
max_n(gn)=g, the maximum processing delay for the flow in the buffer.
It is assumed that a buffer can identify the value of g. Let U and W
be the latency upper and lower bounds guaranteed to the flow by the
network. Let m be the jitter control parameter, W+g <= m.
The rules for the buffer-holding interval decision are given as
follows:
* c1=(b1+m-W),
* cn=max{(bn+g), (c1+an-a1)}, for n > 1.
The second rule governing the cn states that a packet should be held
in the buffer to make its inter-buffer-out time, (cn-c1), equal to
the inter-arrival time, (an-a1). However, when its departure from
the network is too late, the inter-buffer-out time should be larger
than the inter-arrival time, then hold the packet as much as the
maximum processing delay in the buffer, that is, cn=bn+g. The buffer
does not need to know the exact values of an or a1. It is sufficient
to determine the difference between these values, which can be easily
obtained by subtracting the timestamp values of the two packets.
The following theorems holds [ADN].
Theorem 1 (Upper bound of E2E buffered latency). The latency from
the packet arrival to the buffer-out times (cn-an), is upper bounded
by (U-W+m).
Theorem 2 (Lower bound of E2E buffered latency). The latency from
the packet arrival to the buffer-out times (cn-an), is lower bounded
by m.
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Theorem 3 (Upper bound of jitter). The jitter is upper bounded by
max{0, (U+g-m)}.
By setting m=(U+g), we can achieve zero jitter. In this case, the
E2E buffered latency bound becomes (2U+g-W), which is roughly twice
the E2E latency bound. In contrast, if we set m to its minimum
possible value W+g, then the jitter bound becomes (U-W), which is
roughly equal to U, while the E2E buffered latency bound becomes U,
which is the same as the E2E latency bound.
The parameter m directly controls the holding interval of the first
packet. It plays a critical role in determining the jitter and the
buffered latency upper bounds of a flow in the BN framework. The
larger the m, the smaller the jitter bound, and the larger the
latency bound. With a sufficiently large m, we can guarantee zero
jitter, at the cost of an increased latency bound.
5.4. Frequency synchronization between the source and the buffer
Clock drift refers to phenomena wherein a clock does not run at
exactly the same rate as a reference clock. If we do not frequency-
synchronize the clocks of different nodes in a network, clock drift
is unavoidable. Consequently, jitter occurs owing to the clock
frequency difference or clock drift between the source (timestamper)
and the buffer. Therefore, it is recommended to frequency-
synchronize the source (timestamper) and the buffer.
5.5. Omission of the timestamper
For isochronous traffic whose inter-arrival times are well-known
fixed values, and the network can preserve the FIFO property for such
traffic, then the timestampers can be omitted.
Otherwise the FIFO property cannot be guaranteed, then a sequence
number field in the packet header would be enough to replace the
timestamper.
5.6. Mitigation of the increased E2E buffered latency
The increased E2E buffered latency bound by the proposed framework,
from U to almost 2U, can be mitigated by one of the added
functionalities given as follows.
1) First, one can measure the E2E latency of a flow's first packet
exactly, and buffer it to make its E2E buffered latency be U. Then,
by following the rules given in Section 5.3, every subsequent packet
will experience the same E2E buffered latency, which is U, with zero
jitter. An example of the exact latency measurement may be performed
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by time-synchronization between the source (timestamper) and the
buffer. However, how to measure the latency is for further
investigation.
2) Second, one can expedite the first packet's service with a special
treatment, to make its latency lower, compared to the other packets
of the flow. If we can make the first packet's latency to be a small
value d, then every packet will experience the same buffered latency
d+U, with zero jitter. Considering that the E2E latency bound is
calculated from the worst case in which rare events occur
simultaneously, however, the first packet's latency is likely to be
far less than what the bound suggests. Therefore, the special
treatment to the first packet may be ineffective in real
implementations.
5.7. Multi-sources single-destination flows' jitter control
The BN framework can also be used for jitter control among multiple
sources' flows having a single destination. When a session is
composed of more than one sources, physically or virtually separated,
the buffer at the boundary can mitigate the latency variations of
packets from different sources due to different routes or network
treatments. Such a scenario may arise in cases such as
1) that a central unit controls multiple devices for a coordinated
execution in smart factories, or
2) multi-user conferencing applications, in which multiple
devices/users physically separated can have a difficulty in real-
time interactions.
The sources, or the ingress boundary nodes of the network, need to be
synchronized with each other in order for the time-stamps from
separated sources to be able to identify the absolute arrival times.
6. IANA Considerations
There are no IANA actions required by this document.
7. Security Considerations
This section will be described later.
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8. Acknowledgements
9. Contributor
10. References
10.1. Normative References
[I-D.liu-detnet-large-scale-requirements]
Liu, P., Li, Y., Eckert, T. T., Xiong, Q., Ryoo, J.,
zhushiyin, and X. Geng, "Requirements for Large-Scale
Deterministic Networks", Work in Progress, Internet-Draft,
draft-liu-detnet-large-scale-requirements-05, 20 October
2022, <https://datatracker.ietf.org/doc/html/draft-liu-
detnet-large-scale-requirements-05>.
[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>.
[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>.
[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>.
[RFC9320] Finn, N., Le Boudec, J.-Y., Mohammadpour, E., Zhang, J.,
and B. Varga, "Deterministic Networking (DetNet) Bounded
Latency", RFC 9320, DOI 10.17487/RFC9320, November 2022,
<https://www.rfc-editor.org/info/rfc9320>.
10.2. Informative References
[ADN] Joung, J., Kwon, J., Ryoo, J., and T. Cheung,
"Asynchronous Deterministic Network Based on the DiffServ
Architecture", IEEE Access, vol. 10, pp. 15068-15083,
doi:10.1109/ACCESS.2022.3146398, 2022.
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[ANDREWS] Andrews, M., "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.
[BN] Joung, J. and J. Kwon, "Zero jitter for deterministic
networks without time-synchronization", IEEE Access, vol.
9, pp. 49398-49414, doi:10.1109/ACCESS.2021.3068515, 2021.
[BOUILLARD]
Bouillard, A., Boyer, M., and E. Le Corronc,
"Deterministic network calculus: From theory to practical
implementation", in Networks and Telecommunications.
Hoboken, NJ, USA: Wiley, doi: 10.1002/9781119440284, 2018.
[FAIR] Joung, J., "Framework for delay guarantee in multi-domain
networks based on interleaved regulators",
Electronics, vol. 9, no. 3, p. 436,
doi:10.3390/electronics9030436, March 2020.
[I-D.yizhou-detnet-ipv6-options-for-cqf-variant]
Li, Y., Ren, S., Li, G., Yang, F., Ryoo, J., and P. Liu,
"IPv6 Options for Cyclic Queuing and Forwarding Variants",
Work in Progress, Internet-Draft, draft-yizhou-detnet-
ipv6-options-for-cqf-variant-02, 26 April 2023,
<https://datatracker.ietf.org/doc/html/draft-yizhou-
detnet-ipv6-options-for-cqf-variant-02>.
[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>.
[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>.
[KAUR] Kaur, J. and H.M. Vin, "Core-stateless guaranteed rate
scheduling algorithms", in Proc. INFOCOM, vol.3, pp.
1484-1492, 2001.
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[LBF] Clenm, A. and T. Eckert, "High-precision latency
forwarding over packet-programmable networks", NOMS 2020
- IEEE/IFIP Network Operations and Management Symposium,
April 2020.
[LEBOUDEC] Le Boudec, J., "A theory of traffic regulators for
deterministic networks with application to interleaved
regulators", IEEE/ACM Trans. Networking, vol. 26, no. 6,
pp. 2721-2733, doi:10.1109/TNET.2018.2875191, December
2019.
[PAREKH] Parekh, A. and R. Gallager, "A generalized processor
sharing approach to flow control in integrated services
networks: the single-node case", IEEE/ACM Trans.
Networking, vol. 1, no. 3, pp. 344-357, June 1993.
[RFC2212] Shenker, S., Partridge, C., and R. Guerin, "Specification
of Guaranteed Quality of Service", RFC 2212,
DOI 10.17487/RFC2212, September 1997,
<https://www.rfc-editor.org/info/rfc2212>.
[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>.
[STILIADIS-LRS]
Stiliadis, D. and A. Anujan, "Latency-rate servers: A
general model for analysis of traffic scheduling
algorithms", IEEE/ACM Trans. Networking, vol. 6, no. 5,
pp. 611-624, 1998.
[STOICA] Stoica, I. and H. Zhang, "Providing guaranteed services
without per flow management", ACM SIGCOMM Computer
Communication Review, vol. 29, no. 4, pp. 81-94, 1999.
[THOMAS] Thomas, L., Le Boudec, J., and A. Mifdaoui, "On cyclic
dependencies and regulators in time-sensitive networks",
in Proc. IEEE Real-Time Syst. Symp. (RTSS), York, U.K.,
pp. 299-311, December 2019.
[Y.3113] International Telecommunication Union, "Framework for
Latency Guarantee in Large Scale Networks Including
IMT-2020 Network", ITU-T Recommendation Y.3113, February
2021.
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[ZHANG] Zhang, L., "Virtual clock: A new traffic control algorithm
for packet switching networks", in Proc. ACM symposium on
Communications architectures & protocols, pp. 19-29, 1990.
Authors' Addresses
Jinoo Joung
Sangmyung University
Email: jjoung@smu.ac.kr
Jeong-dong Ryoo
ETRI
Email: ryoo@etri.re.kr
Taesik Cheung
ETRI
Email: cts@etri.re.kr
Yizhou Li
Huawei
Email: liyizhou@huawei.com
Peng Liu
China Mobile
Email: liupengyjy@chinamobile.com
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