RFC 9320
Deterministic Networking (DetNet) Bounded Latency
Title Block: RFC 9320 💖 Deterministic Networking (DetNet) Bounded Latency
Okay bestie, let's get into it ✨ This one is RFC 9320, titled Deterministic Networking (DetNet) Bounded Latency. It came out in November 2022 as an Informational doc, so it's not a Standards Track spec 🎀 The authors are N. Finn and J. Zhang from Huawei Technologies Co. Ltd, J.-Y. Le Boudec and E. Mohammadpour from EPFL, and B. Varga from Ericsson. It's published under ISSN 2070-1721, and it doesn't obsolete or update any other RFCs 🦋
Abstract
Okay so this doc is giving a timing model for sources, destinations, and Deterministic Networking (DetNet) transit nodes 🧚 With that model, you get a method for computing end-to-end latency and backlog bounds for different queuing methods. Management and control planes, plus resource reservation algorithms, can use it to get bounded latency and zero congestion loss for the DetNet service. Iconic, honestly 👑
Status of This Memo
This document is not an Internet Standards Track specification. It's published for informational purposes 💅
It's a product of the Internet Engineering Task Force (IETF) and represents the consensus of the IETF community. It got public review and was approved for publication by the Internet Engineering Steering Group (IESG). Not every IESG-approved doc is a candidate for any level of Internet Standard, so check Section 2 of RFC 7841 for that 🙈
For the current status, any errata, and how to give feedback, go to https://www.rfc-editor.org/info/rfc9320 🌸
Copyright Notice
Copyright (c) 2022 IETF Trust and the persons identified as the document authors. All rights reserved 💜
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. Please review those carefully, because they describe your rights and restrictions for this document. Code Components pulled out of this document must include Revised BSD License text as described in Section 4.e of the Trust Legal Provisions, and they come without warranty as described in the Revised BSD License 🔥
Table of Contents
1. Introduction
2. Terminology and Definitions
3. DetNet Bounded Latency Model
3.1. Flow Admission
3.1.1. Static Latency Calculation
3.1.2. Dynamic Latency Calculation
3.2. Relay Node Model
4. Computing End-to-End Delay Bounds
4.1. Non-queuing Delay Bound
4.2. Queuing Delay Bound
4.2.1. Per-Flow Queuing Mechanisms
4.2.2. Aggregate Queuing Mechanisms
4.3. Ingress Considerations
4.4. Interspersed DetNet-Unaware Transit Nodes
5. Achieving Zero Congestion Loss
6. Queuing Techniques
6.1. Queuing Data Model
6.2. Frame Preemption
6.3. Time-Aware Shaper
6.4. Credit-Based Shaper with Asynchronous Traffic Shaping
6.4.1. Delay Bound Calculation
6.4.2. Flow Admission
6.5. Guaranteed Service
6.6. Cyclic Queuing and Forwarding
7. Example Application on DetNet IP Network
8. Security Considerations
9. IANA considerations
10. References
10.1. Normative References
10.2. Informative References
Acknowledgments
Contributors
Authors' Addresses1. Introduction 🦋
Okay so the whole point is this: IETF Deterministic Networking (DetNet) or IEEE 802.1 Time-Sensitive Networking [IEEE8021TSN] can only deliver the DetNet services of bounded latency and zero congestion loss if three things are true 💖
A. Network resources are configured and allocated for the exclusive use of DetNet flows;
B. In the data plane, you can identify the resources that any given packet is going to use; and
C. The detailed behavior of those resources, especially transmission queue selection, is predictable, so latency bounds can be reliably assured.
As [RFC8655] explains, DetNet flows are notably characterized by two things 🎀
- a maximum bandwidth, guaranteed either by the transmitter or by strict input metering, and
- a requirement for a guaranteed worst-case end-to-end latency.
That latency guarantee is what gives the network the chance to supply enough buffer space to guarantee zero congestion loss ✨ This document assumes that the paths of DetNet flows are fixed. Before a DetNet flow gets transmitted, you can calculate end-to-end latency bounds and the amount of buffer space needed at each hop to ensure zero congestion loss. That can be used by the applications identified in [RFC8578] 💅
This document presents a timing model for sources, destinations, and DetNet transit nodes. Using that model, it gives a method for computing end-to-end latency and backlog bounds for various queuing mechanisms that management and control planes can use to provide DetNet quality of service 🌈 The methodology accounts for the possibility of packet reordering within a DetNet node. Bounds on the amount of packet reordering are out of scope for this document and can be found in [PacketReorderingBounds] 🙈 Also, this document references specific queuing mechanisms, mentioned in [RFC8655], as proofs of concept that can control packet transmission at each output port and achieve the DetNet quality of service (QoS) 💜
Using the model in this document, an implementer, user, or standards development organization can select a set of queuing mechanisms for each device in a DetNet network, and select a resource reservation algorithm for that network, so those elements can work together to provide the DetNet service 🧚 Section 7 has an example of the timing model applied to a DetNet IP network with a mix of queuing mechanisms.
This document does not specify any resource reservation protocol or control plane function, and it does not describe all of the requirements for those. What it does describe are requirements for resource reservation methods and for queuing mechanisms that, if met, let them work together 🍓
2. Terminology and Definitions 📚
This document uses the terms defined in [RFC8655]. The following terms are also used here 🌸
T-SPEC TrafficSpecification, as defined in Section 5.5 of [RFC9016].
arrival curve An arrival curve function alpha(t) is an upper bound on the number of bits seen at an observation point within any time interval t.
CQF Cyclic Queuing and Forwarding.
CBS Credit-Based Shaper.
TSN Time-Sensitive Networking.
PREOF A collective name for Packet Replication, Elimination, and Ordering Functions.
POF A Packet Ordering Function is a function that reorders packets within a DetNet flow that are received out of order. This function can be implemented by a DetNet edge node, a DetNet relay node, or an end system.
3. DetNet Bounded Latency Model 💖
3.1. Flow Admission ✨
This document assumes the following paradigm is used to admit DetNet flows 🎀
- Perform any configuration required by the DetNet transit nodes in the network for aggregates of DetNet flows. This configuration is done beforehand and is not tied to any particular DetNet flow.
- Characterize the new DetNet flow, particularly in terms of required bandwidth.
- Establish the path the DetNet flow will take through the network from the source to the destination(s). This can be a point-to-point or a point-to-multipoint path.
- Compute the worst-case end-to-end latency for the DetNet flow using one of the methods below (Sections 3.1.1 and 3.1.2). In the process, determine whether sufficient resources are available for the DetNet flow to guarantee the required latency and to provide zero congestion loss.
- Assuming the resources are available, commit those resources to the DetNet flow. This may require adjusting the parameters that control the filtering and/or queuing mechanisms at each hop along the DetNet flow's path.
This paradigm can be implemented using peer-to-peer protocols or using a central controller. In some situations, a lack of resources can require backtracking and recursing through the list above 🦋
Issues like service preemption of one DetNet flow in favor of another, when resources are scarce, are not considered here. Also not addressed is how to choose the path a DetNet flow takes 🙈
3.1.1. Static Latency Calculation 🌸
The static problem:
Given a network and a set of DetNet flows, compute an end-to-
end latency bound (if computable) for each DetNet flow and
compute the resources, particularly buffer space, required in
each DetNet transit node to achieve zero congestion loss.In this calculation, all of the DetNet flows are known before the calculation starts. This problem is of interest to relatively static networks or static parts of larger networks. It provides bounds on latency and buffer size. The calculations can be extended to provide global optimizations, such as altering the path of one DetNet flow to make resources available to another DetNet flow with tighter constraints 💜
This calculation may be harder to perform than the dynamic calculation (Section 3.1.2) because the DetNet flows passing through one port on a DetNet transit node affect each other's latency. The effects can even be circular, from node A to B to C and back to A 😭 On the other hand, the static calculation can often accommodate queuing methods, such as transmission selection by strict priority, that are unsuitable for the dynamic calculation 🫶
Part 1 of 7. More parts coming, so stay tuned bestie 💅
3.1.2. Dynamic Latency Calculation ✨
okay so here's the dynamic problem 👀
Given a network whose maximum capacity for DetNet flows is bounded by a set of static configuration parameters applied to the DetNet transit nodes, and given just one DetNet flow, compute the worst-case end-to-end latency that can be experienced by that flow, no matter what other DetNet flows (within the network's configured parameters) might be created or deleted in the future. Also, compute the resources, particularly buffer space, required in each DetNet transit node to achieve zero congestion loss.
this calculation is dynamic, bestie 🦋 because DetNet flows can be added or deleted at any time, with minimal computation effort and without messing up the guarantees already given to other DetNet flows. no drama, just vibes 💅
dynamic latency calculation can be built on top of the static one from Section 3.1.1 🧩 when a new DetNet flow is created or deleted, the whole calculation for all DetNet flows gets run again. and if a flow that's already set up would get pushed past its latency requirements by the new request, then the new request can be refused, or some other suitable action can be taken 🙅♀️
the queuing method you pick is everything here 🔥 some queuing methods (for example CQF, Section 6.6) make it easy to configure bounds on the network's capacity and to do independent calculations for each DetNet flow, which is so iconic. other queuing methods (for example strict priority with the credit-based shaper defined in Section 8.6.8.2 of [IEEE8021Q]) can be used for dynamic DetNet flow creation, but they give weaker latency and buffer space guarantees than when that same queuing method is used for static DetNet flow creation (Section 3.1.1) 🥺
3.2. Relay Node Model 🎀
we need a model for how a DetNet transit node operates, so we can define the latency and buffer calculations 🧠 Figure 1 breaks down the per-hop latency a packet experiences as it passes through a DetNet transit node, in terms that work for computing both hop-by-hop latency and per-hop buffer requirements. it's giving engineering diagram ✨
DetNet transit node A DetNet transit node B
+-------------------------+ +------------------------+
| Queuing | | Queuing |
| Regulator subsystem | | Regulator subsystem |
| +-+-+-+-+ +-+-+-+-+ | | +-+-+-+-+ +-+-+-+-+ |
-->+ | | | | | | | | | + +------>+ | | | | | | | | | + +--->
| +-+-+-+-+ +-+-+-+-+ | | +-+-+-+-+ +-+-+-+-+ |
| | | |
+-------------------------+ +------------------------+
|<->|<------>|<------->|<->|<---->|<->|<------>|<------>|<->|<--
2,3 4 5 6 1 2,3 4 5 6 1 2,3
1: Output delay 4: Processing delay
2: Link delay 5: Regulation delay
3: Frame preemption delay 6: Queuing subsystem delay
Figure 1: Timing Model for DetNet or TSNin Figure 1 there are two DetNet transit nodes connected by a link 🔗 the only queues we deal with explicitly are the ones attached to the output port. other queues get modeled as variations in the other delay times 🫶 (like, an input queue could be modeled as a variation in the link delay (2) or the processing delay (4)). there are six delays a packet can hit from hop to hop 👇
- Output delay 📤 this is the time from when a packet gets selected for output from a queue until the first bit of the packet goes out on the physical link. if the queue is directly attached to the physical port, the output delay can be a constant. but in lots of implementations, a multiplexed connection sits between the queuing mechanism and a multi-port Network Interface Card (NIC), and that causes variations in the output delay that are hard for the forwarding node to predict or control 😭
- Link delay 🔗 this is the time from when the first bit of the packet is transmitted until the last bit is received, assuming the transmission isn't suspended by a frame preemption event. this delay has two parts: the first-bit-out to first-bit-in delay, and the first-bit-in to last-bit-in delay, which varies with packet size. the former is typically constant. however, a virtual "link" could show a variable link delay 🌀
- Frame preemption delay ⏸️ if the packet gets interrupted so another packet (or packets) can be transmitted (for example frame preemption, as in [IEEE8023], clause 99), an arbitrary delay can result 🙃
- Processing delay 🧁 this covers the time from when the last bit of the packet is received until the packet is enqueued in the regulator (or in the queuing subsystem if there's no regulator), as shown in Figure 1. this delay can be variable and depends on the details of how the forwarding node operates 🤷♀️
- Regulator queuing delay 🚦 a regulator, also known as a shaper in [RFC2475], delays some or all of the packets in a traffic stream so the stream complies with an arrival curve. an arrival curve 'alpha(t)' is an upper bound on the number of bits observed within any interval t 📈 the regulator delay is the time from when the last bit of a packet is inserted into a regulation queue until the packet is declared eligible under its regulation constraints. we assume this time can be calculated from the details of the regulation policy. if there's no regulation, this time is zero 🙌
- Queuing subsystem delay 🗂️ this is the time a packet spends from being declared eligible until it's selected for output on the next link. we assume this time is calculable from the details of the queuing mechanism. if there's no regulation, this time runs from when the packet is inserted into a queue until it's selected for output on the next link 💖
not shown in Figure 1 are the other output queues that we presume are attached to that same output port as the queue shown. this queue competes with them for transmission opportunities 🥊
in this analysis, the measurement runs from the point where a packet is selected for output in a node to the point where it's selected for output in the next downstream node (that's the definition of a "hop" 🦋). in general, any queue selection method that's suitable for a DetNet network includes a detailed specification of exactly when packets get selected for transmission 📋 any variation in delay times 1-4 means you need extra buffers in the queue 🪣 if all delays 1-4 are constant, then any variation in when packets get inserted into a queue depends entirely on the timing of packet selection in the previous node. if delays 1-4 aren't constant, extra buffers are needed in the queue to absorb those variations. so, the big takeaways:
- Variations in the output delay (1) require buffers to absorb that variation in the next hop, so the output delay variations of the previous hop (on each input port) must be known in order to calculate the buffer space required on this hop. 🧮
- Variations in the processing delay (4) require additional output buffers in the queues of that same DetNet transit node. Depending on the details of the queuing subsystem delay (6) calculations, these variations need not be visible outside the DetNet transit node. 🫧
4. Computing End-to-End Delay Bounds 🌈
4.1. Non-queuing Delay Bound 💅
end-to-end latency bounds can be computed using the delay model in Section 3.2 🧠 and here's the important part: for several queuing mechanisms, the end-to-end latency bound is less than the sum of the per-hop latency bounds 🤯 an end-to-end latency bound for one DetNet flow can be computed as:
end_to_end_delay_bound = non_queuing_delay_bound +
queuing_delay_boundthere are two terms in that formula, and here's how each one gets computed 👇
first, at the h-th hop along the path of this DetNet flow, get an upper-bound per-hop_non_queuing_delay_bound[h] on the sum of the bounds over delays 1, 2, 3, and 4 of Figure 1. these upper bounds are expected to depend on the specific technology of the DetNet transit node at the h-th hop, but not on the T-SPEC of this DetNet flow [RFC9016]. then set non_queuing_delay_bound equal to the sum of per-hop_non_queuing_delay_bound[h] over all hops h 🧁
second, compute queuing_delay_bound as an upper bound on the sum of the queuing delays along the path 🗂️ the value of queuing_delay_bound depends on the information about the arrival curve of this DetNet flow and possibly of other flows in the network, plus the specifics of the queuing mechanisms deployed along the path of this DetNet flow. note that the arrival curve of the DetNet flow at the source is immediately specified by the T-SPEC of this flow 📜 the computation of queuing_delay_bound is described in Section 4.2 as its own section 🫶
4.2. Queuing Delay Bound 🎀
for several queuing mechanisms, queuing_delay_bound is less than the sum of upper bounds on the queuing delays (5 and 6) at every hop 🙌 this happens with (1) per-flow queuing and (2) aggregate queuing with regulators, as explained in Sections 4.2.1, 4.2.2, and 6. for other queuing mechanisms, the only available value of queuing_delay_bound is the sum of the per-hop queuing delay bounds 🧮
the computation of per-hop queuing delay bounds has to account for the fact that the arrival curve of a DetNet flow is no longer satisfied at the ingress of a hop, because burstiness increases as one flow traverses one DetNet transit node 💥 if a regulator is placed at a hop, the arrival curve of a DetNet flow at the entrance of the queuing subsystem of this hop is the one configured at the regulator (also called the shaping curve in [NetCalBook]). otherwise, the arrival curve of the flow can be derived using the delay jitter of the flow from the last regulation point (the last regulator in the path of the flow if there is any, otherwise the source of the flow) to the ingress of the hop. more formally: assume a DetNet flow has an arrival curve at the last regulation point equal to alpha(t), and the delay jitter from the last regulation point to the ingress of the hop is V. then the arrival curve at the ingress of the hop is alpha(t+V) 📈
for example, consider a DetNet flow with T-SPEC Interval: tau, MaxPacketsPerInterval: K, MaxPayloadSize: L at the source ✨ then a leaky-bucket arrival curve for this flow at the source is alpha(t)=r * t+ b, t>0; alpha(0)=0, where r is the rate and b is the bucket size, computed as:
r = K * (L+L') / tau,
b = K * (L+L').where L' is the size of any added networking technology-specific encapsulation (for example MPLS label(s), UDP, or IP headers) 🎁 now, if the flow has a delay jitter of V from the last regulation point to the ingress of a hop, the arrival curve at this point is r * t + b + r * V, which means the burstiness is increased by r*V 😭 more detailed information on arrival curves is available in [NetCalBook] 📚
4.2.1. Per-Flow Queuing Mechanisms ✨
Okay so, per-flow queuing gives every flow its very own queue inside every node 💅 Each queue's service is described with a guaranteed rate and a latency 🎀 For every DetNet flow, you can work out a per-node latency bound and an end-to-end latency bound. You do this from the flow's traffic specification at its source, plus the rates and latencies at all the nodes along its path 🦋 Guaranteed Service [RFC2212] is a real example of this, and its latency bound calculation details are in Section 6.5 💜
4.2.2. Aggregate Queuing Mechanisms 🌸
Now aggregate queuing is the opposite energy 🫶 Multiple flows get bundled into macro-flows, and each macro-flow gets one FIFO queue. A practical example is the credit-based shaper in Section 8.6.8.2 of [IEEE8021Q], where the macro-flow is called a "class" 💖
The big issue here is the burstiness cascade 😭 Individual flows sharing a resource that's dedicated to a macro-flow can end up getting burstier. That extra burstiness can then make other flows downstream of that resource burstier too 💀 Computing delay upper bounds for this is difficult, and in some conditions literally impossible [CharnyDelay] [BennettDelay] 🙈 Also, the bounds you do get depend on the complete configuration. So when one flow gets added, they have to be recomputed (that's the dynamic calculation in Section 3.1.2) 🌈
A fix for the DetNet flows is to reshape them at every hop. You can do this with per-flow regulators (like leaky-bucket shapers), but that requires per-flow queuing and kind of defeats the whole purpose of aggregate queuing 🥲 The alternative is the interleaved regulator, which reshapes individual DetNet flows without per-flow queuing [SpechtUBS] [IEEE8021Qcr] ✨ With an interleaved regulator, the packet at the head of the queue gets regulated based on its (flow) regulation constraints. It's released at the earliest time that's possible without violating the constraint ⭐
One key feature of a per-flow or interleaved regulator is that it does not increase worst-case latency bounds [LeBoudecTheory] 👑 Specifically, when an interleaved regulator is appended to a FIFO subsystem, it does not increase the worst-case delay of that subsystem. In Figure 1, if the order of packets from the output of a queuing subsystem at node A to the entrance of a regulator at node B is preserved, then the regulator does not increase the worst-case latency bounds. This works out if all the systems are FIFO, or if a DetNet Packet Ordering Function (POF) is implemented just before the regulator 🍓 This property does not hold if packet reordering happens between the output of a queuing subsystem and the entrance of the next downstream interleaved regulator. For example, that could happen at a non-FIFO switching fabric 🙈
Figure 2 shows an example of a network with 5 nodes, an aggregate queuing mechanism, and interleaved regulators, just like Figure 1. An end-to-end delay bound for DetNet flow f, traversing nodes 1 to 5, is calculated like this:
end_to_end_latency_bound_of_flow_f = C12 + C23 + C34 + S4In that formula, Cij is a bound on the delay of the queuing subsystem in node i and the interleaved regulator of node j. S4 is a bound on the delay of the queuing subsystem in node 4 for DetNet flow f. Using the delay definitions in Section 3.2, Cij is actually a bound on a sum of delays 1, 2, 3, and 6 of node i, plus delays 4 and 5 of node j. Similarly, S4 is a bound on the sum of delays 1, 2, 3, and 6 of node 4. A practical example of the queuing model and delay calculation is presented Section 6.4 🧚
f
----------------------------->
+---+ +---+ +---+ +---+ +---+
| 1 |---| 2 |---| 3 |---| 4 |---| 5 |
+---+ +---+ +---+ +---+ +---+
\__C12_/\__C23_/\__C34_/\_S4_/
Figure 2: End-to-End Delay Computation ExampleIf packet reordering does not occur, the end-to-end latency bound calculation given here is tighter than what you'd get by adding up the latency bounds of each node on the path of a DetNet flow [TSNwithATS] 🔥
4.3. Ingress Considerations 🚪
A sender can be a DetNet node that uses exactly the same queuing methods as its adjacent DetNet transit node. That way, the latency and buffer bounds calculations at the first hop are indistinguishable from those at a later hop within the DetNet domain 🥰 On the other hand, the sender might be DetNet unaware. In that case, some conditioning of the DetNet flow may be necessary at the ingress DetNet transit node 😬 The ingress conditioning typically consists of the regulators described in Section 3.2 💅
4.4. Interspersed DetNet-Unaware Transit Nodes 🏝️
Sometimes it's desirable to build a network with both DetNet-aware transit nodes and DetNet-unaware transit nodes. It's also desirable for a DetNet flow to cross an island of DetNet-unaware transit nodes while the network can still offer delay and congestion loss guarantees. This is possible under certain conditions 🦋
In general, when a flow passes through a DetNet-unaware island, the island may cause delay variation beyond what DetNet nodes would cause. So the DetNet flow might come out "lumpier" after crossing the DetNet-unaware island 🫠 DetNet guarantees for delay and buffer requirements can still be calculated and met if, and only if, all of the following are true:
- The latency variation across the DetNet-unaware island must be bounded and calculable.
- An ingress conditioning function (Section 4.3) is required at the reentry to the DetNet-aware domain. This will, at the very least, require some extra buffering to handle the additional delay variation, and that further increases the latency bound 📦
The ingress conditioning is exactly the same problem as that of a sender at the edge of the DetNet domain 👯 The requirement for bounds on the latency variation across the DetNet-unaware island is usually the hardest one to meet 😩 Without such a bound, it's obvious that DetNet can't deliver its guarantees. So a DetNet-unaware island that can't offer bounded latency variation cannot be used to carry a DetNet flow 🚫
5. Achieving Zero Congestion Loss 🛑
When the input rate to an output queue exceeds the output rate for a long enough time, the queue must overflow. This is congestion loss, and it's exactly what DetNet is trying to avoid 🙅♀️
To avoid congestion losses, an upper bound on the backlog present in the regulator and queuing subsystem of Figure 1 must be computed during resource reservation. This bound depends on the set of flows that use these queues, the details of the specific queuing mechanism, and an upper bound on the processing delay (4). The queue must contain the packet in transmission, plus all other packets waiting to be selected for output. A conservative backlog bound that applies to all systems can be derived as follows 📊
The backlog bound is counted in data units (bytes, or words of multiple bytes) that are relevant for buffer allocation. For every flow, or aggregate of flows, we need one buffer space for the packet in transmission, plus space for the packets waiting to be selected for output 🧺
Let
total_in_ratebe the sum of the line rates of all input ports that send traffic to this output port. The value oftotal_in_rateis in data units (e.g., bytes) per second.nb_input_portsbe the number of input ports that send traffic to this output port.max_packet_lengthbe the maximum packet size for packets that may be sent to this output port. This is counted in data units.max_delay456be an upper bound, in seconds, on the sum of the processing delay (4) and the queuing delays (5 and 6) for any packet at this output port.
Then, a bound on the backlog of traffic in the queue at this output port is:
backlog_bound = (nb_input_ports * max_packet_length) +
(total_in_rate * max_delay456)The above bound covers the backlog caused by the traffic entering the queue from the input ports of a DetNet node. If the DetNet node also generates packets (for example, creating new packets or replicating arriving packets), the bound must accordingly incorporate the introduced backlog 🌟
6. Queuing Techniques 🎀
In this section, we present a general queuing data model, plus some examples of queuing mechanisms 📚 For simplicity of latency bound computation, we assume a leaky-bucket arrival curve for each DetNet flow at the source. Also, at each DetNet transit node, the service for each queue is abstracted with a minimum guaranteed rate and a latency [NetCalBook] 💖
6.1. Queuing Data Model ✨
Okay bestie, sophisticated queuing is totally available at Layer 3 (L3) 💅 (see [RFC7806] for an overview if you want the tea). Generally, we assume that "Layer 3" queues, shapers, meters, etc., are precisely the "regulators" shown in Figure 1 🎀. The "queuing subsystems" in that figure are FIFO 🫶. They are not just for bridges. They're an essential part of any DetNet transit node 🔥. Lots of implementation examples show that some of the "Layer 3" mechanisms described in documents, like [RFC7806], are often baked into an implementation with the "Layer 2" mechanisms living in the same node too 🧚. So we need an integrated model to predict how all the different queuing mechanisms interact in a network carrying both DetNet flows and non-DetNet flows 👑.
Figure 3 shows the general flow of packets through the queues of a DetNet transit node 🦋. The DetNet packets get mapped to a bunch of regulators. We assume the Packet Replication, Elimination, and Ordering Functions (PREOF) happen before the DetNet packets enter the regulators 💖. Every packet gets assigned to a set of queues. Packets compete to be selected to be passed to queues in the queuing subsystem, and then they get selected again for output from that subsystem 🌸.
|
+--------------------------------V----------------------------------+
| Queue assignment |
+--+------+----------+---------+-----------+-----+-------+-------+--+
| | | | | | | |
+--V-+ +--V-+ +--V--+ +--V--+ +--V--+ | | |
|Flow| |Flow| |Flow | |Flow | |Flow | | | |
| 0 | | 1 | ... | i | | i+1 | ... | n | | | |
| reg| | reg| | reg | | reg | | reg | | | |
+--+-+ +--+-+ +--+--+ +--+--+ +--+--+ | | |
| | | | | | | |
+--V------V----------V--+ +--V-----------V--+ | | |
| Trans. selection | | Trans. select. | | | |
+----------+------------+ +-----+-----------+ | | |
| | | | |
+--V--+ +--V--+ +--V--+ +--V--+ +--V--+
| out | | out | | out | | out | | out |
|queue| |queue| |queue| |queue| |queue|
| 1 | | 2 | | 3 | | 4 | | 5 |
+--+--+ +--+--+ +--+--+ +--+--+ +--+--+
| | | | |
+----------V----------------------V--------------V-------V-------V--+
| Transmission selection |
+---------------------------------+---------------------------------+
|
VFigure 3: IEEE 802.1Q Queuing Model: Data Flow
Some relevant mechanisms are hidden in this figure and happen inside the queue boxes 👀:
- discarding packets because a queue is full
- discarding packets marked "yellow" by a metering function in preference to discarding "green" packets [RFC2697]
Ideally, neither of these actions are performed on DetNet packets 🙈. Full queues for DetNet packets only happen when a DetNet flow is misbehaving, and the DetNet QoS does not include "yellow" service for packets in excess of a committed rate 💀.
The queue assignment function can get pretty complex, even in a bridge [IEEE8021Q], because of the introduction of per-stream filtering and policing ([IEEE8021Q], clause 8.6.5.1) 😭. On top of the Layer 2 priority expressed in the 802.1Q VLAN tag, a DetNet transit node can use the info from this non-exhaustive list to assign a packet to a particular queue ✨:
- input port
- selector based on a rotating schedule that starts at regular, time-synchronized intervals and has nanosecond precision
- MAC addresses, VLAN ID, IP addresses, Layer 4 port numbers, and Differentiated Services Code Point (DSCP) [RFC8939] [RFC8964]
- the queue assignment function can contain metering and policing functions
- MPLS and/or pseudowire labels [RFC6658]
The "Transmission selection" function decides which queue gets to transfer its oldest packet to the output port when a transmission opportunity pops up 🍓.
6.2. Frame Preemption 🦋
In [IEEE8021Q] and [IEEE8023], the transmission of a frame can be interrupted by one or more "express" frames, and then the interrupted frame can continue transmission 🌈. Frame preemption is modeled as two MAC/PHY stacks: one for packets that can be interrupted, and one for packets that can interrupt the interruptible packets 💜. Only one layer of frame preemption is supported. A transmitter cannot have more than one interrupted frame in progress 🙅♀️. DetNet flows typically pass through the interrupting MAC 🫶. For those DetNet flows with T-SPEC, latency bounds can be calculated by the methods in the following sections, which account for the effect of frame preemption according to the specific queuing mechanism used in DetNet nodes 🧮. Best-effort queues pass through the interruptible MAC, so they can be preempted 😌.
6.3. Time-Aware Shaper ⏰
In [IEEE8021Q], the notion of time-scheduling queue gates is described in Section 8.6.8.4 🚦. On each node, transmission selection for packets is controlled by time-synchronized gates, and each output queue is associated with a gate 🌸. A gate can be either open or closed, and its state is determined by the gate control list (GCL). The GCL specifies the opening and closing times of the gates 🕰️. The design of the GCL has to satisfy the requirement of latency upper bounds for all DetNet flows. That means DetNet flows that traverse a network using this kind of shaper must have bounded latency, as long as the traffic and nodes are conformant 💅✨.
Note that scheduled traffic service relies on a synchronized network and coordinated GCL configuration 🔗. Synthesizing the GCL across multiple nodes in a network is a scheduling problem that considers all DetNet flows traversing the network, and it is nondeterministic polynomial-time hard (NP-hard) [Sch8021Qbv] 🤯. Also, at the time of writing, scheduled traffic service supports no more than eight traffic queues, typically using up to seven priority queues and at least one best effort 🧁.
6.4. Credit-Based Shaper with Asynchronous Traffic Shaping ✨
Okay bestie, this model assumes the DetNet nodes are FIFO 💅. We look at four traffic classes (Definition 3.268 of [IEEE8021Q]): control-data traffic (CDT), class A, class B, and best effort (BE), ranked from highest priority to lowest. Classes A and B are DetNet flows that matter less than CDT, like studio audio and video in IEEE 802.1BA Audio-Video-Bridging 🎀. This model is a subset of Time-Sensitive Networking, as we'll see next 🦋.
Based on the timing model in Figure 1, contention only happens at the output port of a DetNet transit node 👀, so the rest of this subsection zooms in on the regulator and queuing subsystem in that output port. The input flows are identified using the information in (Section 5.1 of [RFC8939]). Then they get aggregated into eight macro-flows based on their service requirements, and each macro-flow is a class. The output port does aggregate scheduling with eight queues (queuing subsystems): one for CDT, one for class A, one for class B, and five for BE traffic, called BE0-BE4. The queuing policy for each one is FIFO.
On top of that, each output port also does per-flow regulation for class A and B flows using an interleaved regulator (IR). This regulation is called asynchronous traffic shaping [IEEE8021Qcr]. So each output port of a node has one interleaved regulator per input port and per class, and the IR is the regulator shown in Figure 1. Figure 4 has the full picture of scheduling and regulation at a node output port. Packets that arrive at a node input port for a given class get enqueued in the matching IR at the output port. Then packets from all flows, including CDT and BE, get enqueued in a queuing subsystem. There's no regulator for CDT and BE flows 🙈.
+--+ +--+ +--+ +--+
| | | | | | | |
|IR| |IR| |IR| |IR|
| | | | | | | |
+-++XXX++-+ +-++XXX++-+
| | | |
| | | |
+---+ +-v-XXX-v-+ +-v-XXX-v-+ +-----+ +-----+ +-----+ +-----+ +-----+
| | | | | | |Class| |Class| |Class| |Class| |Class|
|CDT| | Class A | | Class B | | BE4 | | BE3 | | BE2 | | BE1 | | BE0 |
| | | | | | | | | | | | | | | |
+-+-+ +----+----+ +----+----+ +--+--+ +--+--+ +--+--+ +--+--+ +--+--+
| | | | | | | |
| +-v-+ +-v-+ | | | | |
| |CBS| |CBS| | | | | |
| +-+-+ +-+-+ | | | | |
| | | | | | | |
+-v--------v-----------v---------v-------V-------v-------v-------v--+
| Strict Priority selection |
+--------------------------------+----------------------------------+
|
V
Figure 4: The Architecture of an Output Port inside a Relay Node with
Interleaved Regulators (IRs) and a Credit-Based Shaper (CBS)Each queuing subsystem for classes A and B contains a credit-based shaper (CBS) 🌸. The CBS serves a packet from a class according to that class's available credit. As described in Section 8.6.8.2 and Annex L.1 of [IEEE8021Q], the credit for each class A or B grows based on the idle slope (the guaranteed rate) and shrinks based on the sendslope (usually the gap between the guaranteed and output link rates). Both of those are CBS parameters. CDT and BE0-BE4 each get their own separate queuing subsystem. Then packets from all flows go through a transmission selection subsystem that serves each class based on its priority. All subsystems are non-preemptive.
Guarantees for class A and B traffic can be provided only if CDT is bounded 🚨. It's assumed CDT has a leaky-bucket arrival curve with two parameters:r_has rate andb_has bucket size. So the amount of bits entering a node within a time intervaltis bounded byr_h * t + b_h.
Additionally, class A and B flows are also regulated at their source according to a leaky-bucket arrival curve. At the source, the traffic satisfies its regulation constraint, which means the delay from the interleaved regulator at the source is ignored ✨.
At each DetNet transit node that implements an interleaved regulator, packets from multiple flows are processed in one FIFO queue. The packet at the head of the queue gets regulated based on its leaky-bucket parameters. It's released at the earliest time that's possible without breaking the constraint 🦋.
The regulation parameters for a flow (leaky-bucket rate and bucket size) are the same at its source and at all DetNet transit nodes along its path when all clocks are perfect. But in reality, there's clock non-ideality all over the DetNet domain, even with clock synchronization 😭. That causes inaccuracy in the rates configured at the regulators, which may lead to network instability. To avoid instability, the rates are set as the source rates with some positive margin when configuring regulators. [ThomasTime] describes this issue and provides solutions to it 💜.
6.4.1. Delay Bound Calculation 🧮
A delay bound of the queuing subsystem ((4) in Figure 1) of a given DetNet node for a flow of class A or B can be computed if the following condition holds:
The sum of leaky-bucket rates of all flows of this class at this
transit node <= R, where R is given below for every classIf the condition holds, the delay bound for a flow of class X (A or B) is d_X and is calculated as:
d_X = T_X + (b_t_X-L_min_X)/R_X - L_min_X/cwhere L_min_X is the minimum packet lengths of class X (A or B); c is the output link transmission rate; and b_t_X is the sum of the b term (bucket size) for all the flows of the class X. R_X and T_X are calculated as follows for class A and B, separately 💖.
If the flow is of class A:
R_A = I_A * (c-r_h)/ c
T_A = (L_nA + b_h + r_h * L_n/c)/(c-r_h)where I_A is the idle slope for class A; L_nA is the maximum packet length of class B and BE packets; L_n is the maximum packet length of classes A, B, and BE; and r_h is the rate and b_h is the bucket size of CDT leaky-bucket arrival curve.
If the flow is of class B:
R_B = I_B * (c-r_h)/ c
T_B = (L_BE + L_A + L_nA * I_A/(c_h-I_A) + b_h + r_h * L_n/
c)/(c-r_h)where I_B is the idle slope for class B; L_A is the maximum packet length of class A; and L_BE is the maximum packet length of class BE.
Then, as discussed in Section 4.2.2, an interleaved regulator does not increase the delay bound of the upstream queuing subsystem. So an end-to-end delay bound for a DetNet flow of class X (A or B) is the sum of d_X_i for all node i in the path of the flow, where d_X_i is the delay bound of the queuing subsystem in node i, which is computed as above. Using the notation in Section 4.2.2, the delay bound of the queuing subsystem in a node i and interleaved regulator in node j, i.e., Cij, is:
Cij = d_X_iMore information on delay analysis in such a DetNet transit node is described in [TSNwithATS] 🌈.
6.4.2. Flow Admission 🎀
The delay bound calculation requires some information about each node. For each node, it is required to know the idle slope of the CBS for each class A and B (I_A and I_B), as well as the transmission rate of the output link (c). Besides that, it's necessary to have the information on each class, meaning the maximum packet length of classes A, B, and BE. Moreover, the leaky-bucket parameters of CDT (r_h, b_h) must be known 🧠. To admit a flow or flows of classes A and B, their delay requirements must be guaranteed not to be violated. As described in Section 3.1, the two problems (static and dynamic) are addressed separately. In either of the problems, the rate and delay must be guaranteed. Thus,
The static admission control: The leaky-bucket parameters of all class A or B flows are known, so for each flow f of either class A or B, a delay bound can be calculated. The computed delay bound for every flow of class A or B must not be more than its delay requirement. Moreover, the sum of the rate of each flow (r_f) must not be more than the rate allocated to each class (R). If these two conditions hold, the configuration is declared admissible ✅.
The dynamic admission control: For dynamic admission control, we allocate a static value for rate (R) and a maximum bucket size (b_t) to every node and each class A or B. In addition, for every node and each class A or B, two counters are maintained. R_acc is equal to the sum of the leaky-bucket rates of all flows of this class already admitted at this node. At all times, we must have:
R_acc <= R, (Eq. 1)b_acc is equal to the sum of the bucket sizes of all flows of this class already admitted at this node. At all times, we must have:
b_acc <= b_t. (Eq. 2)A new class A or B flow is admitted at this node if Eqs. (1) and (2) continue to be satisfied after adding its leaky-bucket rate and bucket size to R_acc and b_acc. A class A or B flow is admitted in the network if it is admitted at all nodes along its path. When this happens, all variables R_acc and b_acc along its path must be incremented to reflect the addition of the flow. Similarly, when a class A or B flow leaves the network, all variables R_acc and b_acc along its path must be decremented to reflect the removal of the flow 🔥.
The choice of the static values of R and b_t at all nodes and classes must be done in a prior configuration phase. R controls the bandwidth allocated to this class at this node, and b_t affects the delay bound and the buffer requirement. The value of R must be set such that:
R <= I_X*(c-r_h)/cwhere I_X is the idleslope of credit-based shaper for class X={A,B}, c is the transmission rate of the output link, and r_h is the leaky-bucket rate of the CDT class 💅✨
6.5. Guaranteed Service 🎀
okay so bestie, the Guaranteed Service is defined in [RFC2212] and it is literally the main character of resource reservations 💅. The flow at the source has a leaky-bucket arrival curve with two parameters: r as rate and b as bucket size. In other words, the amount of bits entering a node within a time interval t is bounded by r * t + b ✨.
If a resource reservation on a path is applied, a node provides a guaranteed rate R and a maximum service latency of T 🦋. This can be read as: the bits might have to wait up to T before being served at a rate greater than or equal to R. The delay bound of the flow traversing the node is T + b / R 💖.
Now let's zoom out to a whole path 🌈. Consider a Guaranteed Service [RFC2212] path with a sequence of nodes, where the i-th node provides a guaranteed rate R_i and a maximum service latency of T_i. Then the end-to-end delay bound for a flow on this path can be calculated as sum(T_i) + b / min(R_i) 🧚.
The delay bound I just showed you is the simple version of Guaranteed Service 🌸. It only works when you have a guaranteed rate, a maximum service latency, and a leaky-bucket arrival curve. If more information about the flow is known, like the peak rate, the delay bound gets more complicated 🙈. The details live in [RFC2212] and Section 1.4.1 of [NetCalBook], so go check those if you want the full tea ☕.
6.6. Cyclic Queuing and Forwarding 🔥
okay this one is so iconic 😭. Annex T of [IEEE8021Q] describes Cyclic Queuing and Forwarding (CQF), which gives you bounded latency and zero congestion loss by using the time-scheduled gates of Section 8.6.8.4 of [IEEE8021Q] 👑. For a given class of DetNet flows, a set of two or more buffers is provided at the output queue layer of Figure 3. A cycle time T_c is configured for each class of DetNet flows c, and all of the buffer sets in a class of DetNet flows swap buffers simultaneously throughout the DetNet domain at that cycle rate, all in phase 🫶. In this mechanism, the regulator (as mentioned in Figure 1) is not required 🙅♀️.
In the case of two-buffer CQF, each class of DetNet flows c has two buffers, called buffer1 and buffer2 🍓. In a cycle (i), when buffer1 accumulates received packets from the node's reception ports, buffer2 transmits the packets already stored from the previous cycle (i-1). In the next cycle (i+1), buffer2 stores the received packets and buffer1 transmits the packets received in cycle (i). The duration of each cycle is T_c ⏰.
The cycle time T_c has to be chosen really carefully 🥺. It needs to be large enough to fit all the DetNet traffic, plus at least one maximum packet (or fragment) size from lower priority queues, which might be received within a cycle. The value of T_c also includes a time interval called dead time (DT), which is the sum of delays 1, 2, 3, and 4 defined in Figure 1. The value of DT guarantees that the last packet of one cycle in a node is fully delivered to a buffer of the next node in the same cycle 💜. A two-buffer CQF is recommended if DT is small compared to T_c. For a large DT, CQF with more buffers can be used, and a cycle identification label can be added to the packets ✨.
The per-hop latency is determined by the cycle time T_c: a packet transmitted from a node at cycle (i) is transmitted from the next node at cycle (i+1) 🦋. So if the packet traverses h hops, the maximum latency it experiences runs from the beginning of cycle (i) to the end of cycle (i+h). The minimum latency runs from the end of cycle (i), before the DT, to the beginning of cycle (i+h) 🌈. Therefore, the maximum latency is:
(h+1) T_cand the minimum latency is:
(h-1) T_c + DTIngress conditioning (Section 4.3) may be required if the source of a DetNet flow does not itself employ CQF 🫧. Since there are no per-flow parameters in the CQF technique, per-hop configuration is not required in the CQF forwarding nodes 💅.
7. Example Application on DetNet IP Network 🌷
This section gives an example application of the timing model presented in this document to control the admission of a DetNet flow on a DetNet-enabled IP network 🧚♀️. Consider Figure 5, taken from Section 3 of [RFC8939], which shows a simple IP network:
- End system 1 implements Guaranteed Service [RFC2212], as in Section 6.5, between itself and relay node 1. 🎀
- Sub-network 1 is a TSN network. The nodes in sub-network 1 implement credit-based shapers with asynchronous traffic shaping, as in Section 6.4. 🦋
- Sub-network 2 is a TSN network. The nodes in sub-network 2 implement Cyclic Queuing and Forwarding with two buffers, as in Section 6.6. 💖
- The relay nodes 1 and 2 implement credit-based shapers with asynchronous traffic shaping, as in Section 6.4. They also perform the aggregation and mapping of IP DetNet flows to TSN streams (Section 4.4 of [RFC9023]). 👑
DetNet IP Relay Relay DetNet IP
End System Node 1 Node 2 End System
1 2
+----------+ +----------+
| Appl. |<------------ End-to-End Service ----------->| Appl. |
+----------+ ............ ........... +----------+
| Service |<-: Service :-- DetNet flow --: Service :->| Service |
+----------+ +----------+ +----------+ +----------+
|Forwarding| |Forwarding| |Forwarding| |Forwarding|
+--------.-+ +-.------.-+ +-.---.----+ +-------.--+
: Link : \ ,-----. / \ ,-----. /
+......+ +----[ Sub- ]----+ +-[ Sub- ]-+
[Network] [Network]
`--1--' `--2--'
|<--------------------- DetNet IP --------------------->|
|<--- d1 --->|<--------------- d2_p --------------->|<-- d3_p -->|
Figure 5: A Simple DetNet-Enabled IP Network, Taken from RFC 8939Consider a fully centralized control plane for the network of Figure 5, as described in Section 3.2 of [DETNET-CONTROL-PLANE] 🧠. Suppose end system 1 wants to create a DetNet flow with a traffic specification destined to end system 2, with an end-to-end delay bound requirement D 💌. So the control plane receives a flow establishment request and calculates a number of valid paths through the network (Section 3.2 of [DETNET-CONTROL-PLANE]). To select a proper path, the control plane needs to compute an end-to-end delay bound at every node of each selected path p 🔍.
The end-to-end delay bound is d1 + d2_p + d3_p, where d1 is the delay bound from end system 1 to the entrance of relay node 1, d2_p is the delay bound for path p from relay node 1 to the entrance of the first node in sub-network 2, and d3_p is the delay bound of path p from the first node in sub-network 2 to end system 2 🫶. The computation of d1 is explained in Section 6.5. Since relay node 1, sub-network 1, and relay node 2 implement aggregate queuing, we use the results in Sections 4.2.2 and 6.4 to compute d2_p for the path p. Finally, d3_p is computed using the delay bound computation of Section 6.6. Any path p such that d1 + d2_p + d3_p <= D satisfies the delay bound requirement of the flow ✅. If there is no such path, the control plane may compute a new set of valid paths and redo the delay bound computation, or reject the DetNet flow 🙃.
As soon as the control plane selects a path that satisfies the delay bound constraint, it allocates and reserves the resources in the path for the DetNet flow (Section 4.2 of [DETNET-CONTROL-PLANE]) 🎉.
8. Security Considerations 🔐
Okay bestie, this part is SERIOUS so listen up 🚨. Detailed security considerations for DetNet are cataloged in [RFC9055], and more general security considerations are described in [RFC8655] 📚.
Security aspects that are unique to DetNet are those whose aim is to provide the specific QoS aspects of DetNet, specifically bounded end-to-end delivery latency and zero congestion loss. Achieving such loss rates and bounded latency may not be possible in the face of a highly capable adversary, such as the one envisioned by the Internet Threat Model of BCP 72 [RFC3552], which can arbitrarily drop or delay any or all traffic 😱. In order to present meaningful security considerations, we consider a somewhat weaker attacker who does not control the physical links of the DetNet domain but may have the ability to control or change the behavior of some resources within the boundary of the DetNet domain 🕵️♀️.
Latency bound calculations use parameters that reflect physical quantities. If an attacker finds a way to change the physical quantities, unknown to the control and management planes, the latency calculations fail and may result in latency violation and/or congestion losses 💀. An example of such an attack is to make some traffic sources under the control of the attacker send more traffic than their assumed T-SPECs. This type of attack is typically avoided by ingress conditioning at the edge of a DetNet domain. However, it must be insured that such ingress conditioning is done per flow and that the buffers are segregated, such that if one flow exceeds its T-SPEC, it does not cause buffer overflow for other flows 🚫.
Some queuing mechanisms require time synchronization and operate correctly only if the time synchronization works correctly. In the case of CQF, the correct alignment of cycles can fail if an attack against time synchronization fools a node into having an incorrect offset. Some of these attacks can be prevented by cryptographic authentication, as in Annex K of [IEEE1588] for the Precision Time Protocol (PTP) 🔑. However, attacks that change the physical latency of the links used by the time synchronization protocol are still possible even if the time synchronization protocol is protected by authentication and cryptography [DelayAttack] 😭. Such attacks can be detected only by their effects on latency bound violations and congestion losses, which do not occur in normal DetNet operation 👀.
9. IANA considerations 🌸
This document has no IANA actions. 💅
10. References 📖
10.1. Normative References 📚✨
okay bestie, these are the docs you have to read before the rest of the spec makes sense 🫶 (normative = the non-negotiable stuff, no cap)
[IEEE8021Q]: IEEE, "IEEE Standard for Local and Metropolitan Area Networks--Bridges and Bridged Networks", IEEE Std 802.1Q-2018, DOI 10.1109/IEEESTD.2018.8403927, July 2018, <https://ieeexplore.ieee.org/document/8403927>.
[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>.
[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>.
[RFC6658]: Bryant, S., Ed., Martini, L., Swallow, G., and A. Malis, "Packet Pseudowire Encapsulation over an MPLS PSN", RFC 6658, DOI 10.17487/RFC6658, July 2012, <https://www.rfc-editor.org/info/rfc6658>.
[RFC7806]: Baker, F. and R. Pan, "On Queuing, Marking, and Dropping", RFC 7806, DOI 10.17487/RFC7806, April 2016, <https://www.rfc-editor.org/info/rfc7806>.
[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>.
[RFC8939]: Varga, B., Ed., Farkas, J., Berger, L., Fedyk, D., and S. Bryant, "Deterministic Networking (DetNet) Data Plane: IP", RFC 8939, DOI 10.17487/RFC8939, November 2020, <https://www.rfc-editor.org/info/rfc8939>.
[RFC8964]: Varga, B., Ed., Farkas, J., Berger, L., Malis, A., Bryant, S., and J. Korhonen, "Deterministic Networking (DetNet) Data Plane: MPLS", RFC 8964, DOI 10.17487/RFC8964, January 2021, <https://www.rfc-editor.org/info/rfc8964>.
[RFC9016]: Varga, B., Farkas, J., Cummings, R., Jiang, Y., and D. Fedyk, "Flow and Service Information Model for Deterministic Networking (DetNet)", RFC 9016, DOI 10.17487/RFC9016, March 2021, <https://www.rfc-editor.org/info/rfc9016>.
10.2. Informative References 🌸
these ones are the extra reading 🤓💜 super helpful for going deeper, but you don't need them to get the core idea
[BennettDelay]: Bennett, J. C. R., Benson, K., Charny, A., Courtney, W. F., and J.-Y. Le Boudec, "Delay jitter bounds and packet scale rate guarantee for expedited forwarding", DOI 10.1109/TNET.2002.801404, August 2002, <https://dl.acm.org/citation.cfm?id=581870>.
[CharnyDelay]: Charny, A. and J.-Y. Le Boudec, "Delay Bounds in a Network with Aggregate Scheduling", DOI 10.1007/3-540-39939-9_1, September 2002, <https://link.springer.com/chapter/10.1007/3-540-39939-9_1>.
[DelayAttack]: Barreto, S., Suresh, A., and J. L. Boudec, "Cyber-attack on packet-based time synchronization protocols: The undetectable Delay Box", DOI 10.1109/I2MTC.2016.7520408, May 2016, <https://ieeexplore.ieee.org/document/7520408>.
[DETNET-CONTROL-PLANE]: Malis, A., Geng, A., Ed., Chen, M., Qin, F., and B. Varga, "Deterministic Networking (DetNet) Controller Plane Framework", Work in Progress, Internet-Draft, draft-ietf-detnet-controller-plane-framework-02, 28 June 2022, <https://datatracker.ietf.org/doc/html/draft-ietf-detnet-controller-plane-framework-02>.
[IEEE1588]: IEEE, "IEEE Standard for a Precision Clock Synchronization Protocol for Networked Measurement and Control Systems", IEEE Std 1588-2008, DOI 10.1109/IEEESTD.2008.4579760, July 2008, <https://ieeexplore.ieee.org/document/4579760>.
[IEEE8021Qcr]: IEEE 802.1, "802.1Qcr-2020 - IEEE Standard for Local and Metropolitan Area Networks--Bridges and Bridged Networks Amendment 34:Asynchronous Traffic Shaping", November 2020, <https://ieeexplore.ieee.org/document/9253013>.
[IEEE8021TSN]: IEEE 802.1, "802.1 Time-Sensitive Networking (TSN) Task Group", <https://1.ieee802.org/tsn/>.
[IEEE8023]: IEEE, "IEEE Standard for Ethernet", IEEE Std 802.3-2018, DOI 10.1109/IEEESTD.2018.8457469, August 2018, <http://ieeexplore.ieee.org/document/8457469>.
[LeBoudecTheory]: Le Boudec, J.-Y., "A Theory of Traffic Regulators for Deterministic Networks With Application to Interleaved Regulators", DOI 10.1109/TNET.2018.2875191, November 2018, <https://ieeexplore.ieee.org/document/8519761>.
[NetCalBook]: Le Boudec, J.-Y. and P. Thiran, "Network Calculus: A Theory of Deterministic Queuing Systems for the Internet", Springer Science & Business Media, vol. 2050, 2001, <https://leboudec.github.io/netcal/latex/netCalBook.pdf>.
[PacketReorderingBounds]: Mohammadpour, E. and J.-Y. Le Boudec, "On Packet Reordering in Time-Sensitive Networks", DOI 10.1109/TNET.2021.3129590, December 2021, <https://ieeexplore.ieee.org/document/9640523>.
[RFC2697]: Heinanen, J. and R. Guerin, "A Single Rate Three Color Marker", RFC 2697, DOI 10.17487/RFC2697, September 1999, <https://www.rfc-editor.org/info/rfc2697>.
[RFC3552]: Rescorla, E. and B. Korver, "Guidelines for Writing RFC Text on Security Considerations", BCP 72, RFC 3552, DOI 10.17487/RFC3552, July 2003, <https://www.rfc-editor.org/info/rfc3552>.
[RFC8578]: Grossman, E., Ed., "Deterministic Networking Use Cases", RFC 8578, DOI 10.17487/RFC8578, May 2019, <https://www.rfc-editor.org/info/rfc8578>.
[RFC9023]: Varga, B., Ed., Farkas, J., Malis, A., and S. Bryant, "Deterministic Networking (DetNet) Data Plane: IP over IEEE 802.1 Time-Sensitive Networking (TSN)", RFC 9023, DOI 10.17487/RFC9023, June 2021, <https://www.rfc-editor.org/info/rfc9023>.
[RFC9055]: Grossman, E., Ed., Mizrahi, T., and A. Hacker, "Deterministic Networking (DetNet) Security Considerations", RFC 9055, DOI 10.17487/RFC9055, June 2021, <https://www.rfc-editor.org/info/rfc9055>.
[Sch8021Qbv]: Craciunas, S., Oliver, R., Chmelik, M., and W. Steiner, "Scheduling Real-Time Communication in IEEE 802.1Qbv Time Sensitive Networks", DOI 10.1145/2997465.2997470, October 2016, <https://dl.acm.org/doi/10.1145/2997465.2997470>.
[SpechtUBS]: Specht, J. and S. Samii, "Urgency-Based Scheduler for Time-Sensitive Switched Ethernet Networks", DOI 10.1109/ECRTS.2016.27, July 2016, <https://ieeexplore.ieee.org/abstract/document/7557870>.
[ThomasTime]: Thomas, L. and J.-Y. Le Boudec, "On Time Synchronization Issues in Time-Sensitive Networks with Regulators and Nonideal Clocks", DOI 10.1145/3393691.339420, June 2020, <https://dl.acm.org/doi/10.1145/3393691.3394206>.
[TSNwithATS]: Mohammadpour, E., Stai, E., Mohiuddin, M., and J.-Y. Le Boudec, "Latency and Backlog Bounds in Time-Sensitive Networking with Credit Based Shapers and Asynchronous Traffic Shaping", DOI 10.1109/ITC30.2018.10053, September 2018, <https://ieeexplore.ieee.org/document/8493026>.
Acknowledgments 💖
huge thank-you to Lou Berger, Tony Przygienda, John Scudder, Watson Ladd, Yoshifumi Nishida, Ralf Weber, Robert Sparks, Gyan Mishra, Martin Duke, Éric Vyncke, Lars Eggert, Roman Danyliw, and Paul Wouters for their useful feedback on this document 🙌✨
Contributors 🎀
RFC 7322 limits the number of authors listed on the front page to a maximum of 5. The editor wishes to thank and acknowledge the following author for contributing text to this document:
Janos Farkas
Ericsson
Email: janos.farkas@ericsson.comAuthors' Addresses 🦋
Norman Finn
Huawei Technologies Co. Ltd
3101 Rio Way
Spring Valley, California 91977
United States of America
Phone: +1 925 980 6430
Email: nfinn@nfinnconsulting.comJean-Yves Le Boudec
EPFL
IC Station 14
CH-1015 Lausanne
Switzerland
Email: jean-yves.leboudec@epfl.chEhsan Mohammadpour
EPFL
IC Station 14
CH-1015 Lausanne
Switzerland
Email: ehsan.mohammadpour@epfl.chJiayi Zhang
Huawei Technologies Co. Ltd
Q27, No.156 Beiqing Road
Beijing
100095
China
Email: zhangjiayi11@huawei.comBalázs Varga
Ericsson
Budapest
Konyves Kálmán krt. 11/B
1097
Hungary
Email: balazs.a.varga@ericsson.com📦 where this page comes from
- ietf: rfc9320 2022-11
- 💖 girlified by claude-haiku-5-5 on : a language model's rewrite of the original, under its terms