Latency Guarantee with Stateless Fair Queuing
draft-joung-detnet-stateless-fair-queuing-03
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| Document | Type | Active Internet-Draft (individual) | |
|---|---|---|---|
| Authors | Jinoo Joung , Jeong-dong Ryoo , Taesik Cheung , Yizhou Li , Peng Liu | ||
| Last updated | 2024-07-02 | ||
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draft-joung-detnet-stateless-fair-queuing-03
DetNet Working Group J. Joung
Internet-Draft Sangmyung University
Intended status: Standards Track J. Ryoo
Expires: 3 January 2025 T. Cheung
ETRI
Y. Li
Huawei
P. Liu
China Mobile
2 July 2024
Latency Guarantee with Stateless Fair Queuing
draft-joung-detnet-stateless-fair-queuing-03
Abstract
This document specifies the framework and the operational procedure
for deterministic networking with a set of work conserving packet
schedulers that guarantees end-to-end (E2E) latency bounds to flows.
The schedulers in core nodes do not need to maintain flow states.
Instead, the entrance node of a flow marks an ideal service
completion time according to a fluid model, called Finish Time (FT),
of a packet in the packet header. The subsequent core nodes update
FT by adding a delay factor, which is a function of the flow and
upstream nodes. The packets in the queue of the scheduler are served
in the ascending order of FT. This mechanism is called the stateless
fair queuing. The result is that flows are isolated from each other
almost perfectly. The latency bound of a flow depends only on the
flow's intrinsic parameters, except the maximum packet length among
other flows sharing each output link with the flow.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
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material or to cite them other than as "work in progress."
This Internet-Draft will expire on 3 January 2025.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1. Terms Used in This Document . . . . . . . . . . . . . . . 4
2.2. Abbreviations . . . . . . . . . . . . . . . . . . . . . . 4
3. Conventions Used in This Document . . . . . . . . . . . . . . 4
4. Fair Queuing Schedulers . . . . . . . . . . . . . . . . . . . 4
5. Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . 6
6. Work Conserving Stateless Core Fair Queuing (C-SCORE) . . . . 7
6.1. Framework . . . . . . . . . . . . . . . . . . . . . . . . 7
6.2. E2E Latency Bound . . . . . . . . . . . . . . . . . . . . 8
6.3. Operational Procedure . . . . . . . . . . . . . . . . . . 9
6.3.1. Metadata . . . . . . . . . . . . . . . . . . . . . . 10
6.3.2. Network Configuration for latency guarantee . . . . . 10
6.3.3. Role of entrance node for generation and update of
FT . . . . . . . . . . . . . . . . . . . . . . . . . 11
6.3.4. Role of core node for update of FT . . . . . . . . . 11
6.3.5. Mitigation of complexity in entrance node . . . . . . 11
6.3.6. Compensation of time difference between nodes . . . . 12
6.4. Characteristics . . . . . . . . . . . . . . . . . . . . . 12
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 13
8. Security Considerations . . . . . . . . . . . . . . . . . . . 13
9. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 13
10. Contributor . . . . . . . . . . . . . . . . . . . . . . . . . 13
11. References . . . . . . . . . . . . . . . . . . . . . . . . . 13
11.1. Normative References . . . . . . . . . . . . . . . . . . 13
11.2. Informative References . . . . . . . . . . . . . . . . . 14
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 15
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1. Introduction
There are emerging applications that require both latency and jitter
bounds in large-scale networks. One of the key mechanisms to the
latency and jitter performance of a network is the packet scheduling.
Our objective is to specify a scheduling mechanism that can
completely isolate a flow from other flows that are sharing a link.
An ideal flow isolation would be achieved, if an imaginary link is
dedicated solely to the flow, with the capacity equal to the
allocated service rate to the flow. In this case the latency upper
bound is a function of the parameters, which depend only on the flow.
In large-scale networks, 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].
A class of schedulers called Fair Queuing (FQ) 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 FQ [PAREKH]. In FQ, the ideal service
completion time, called Finish Time (FT), of a packet is obtained
from an imaginary system which can provide the ideal flow isolation.
Packets in the buffer are served in an increasing order of the FT.
When this mechanism is applied, the end-to-end (E2E) latency bound of
a flow is similar to that in the ideally isolated system. However,
the FT of the previous packet within a flow has to be remembered for
the calculation of the current packet's FT. This information can be
seen as the flow state. The complexity of managing such information
for a large number of flows can be a burden, so the FQ has not been
usually adopted in practice.
This document specifies a framework for approximating the FQ
scheduler in core nodes. It also specifies the operational procedure
based on this framework. The edge node through which a flow enters a
network is called the entrance node. The entrance node for a flow
generates FT for a packet and records it in the packet. A core node,
based on these records, updates FT by adding a delay factor that is a
function of parameters of nodes and the flow. The proposed framework
is called work conserving stateless core fair queuing (C-SCORE)
[C-SCORE]. C-SCORE is work conserving and has the property that, for
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a certain choice of the delay factor, the expression for E2E latency
bound can be found. This E2E latency bound function is the same as
that of a network with stateful FQ schedulers in all the nodes.
The key component of C-SCORE is the packet state that is carried as
metadata. C-SCORE does not need to maintain flow states at core
nodes, yet it works as one of the FQ 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.
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. Fair Queuing Schedulers
Generalized processor sharing (GPS) suggested a paradigm for a fair
service for flows as fluid. Packetized GPS (PGPS), which implemented
GPS in the realistic packet-based environment, played a pioneering
role in this type of packet-based schedulers [PAREKH]. PGPS
determines the service order of packets in ascending order of the FT
derived by the following equation.
F(p) = max{F(p-1), V(A(p))}+L(p)/r, (1)
where p and p-1 are the pth and (p-1)th packets of a flow, F(p) is
the FT, A(p) is the arrival time, L(p) is the length of the packet p,
and r is the service rate allocated to the flow. Note that the index
for the flow i is omitted. V(t) is called the virtual time function
[PAREKH]. and is a value representing the current system progress at
time t. If the backlogged flows almost fill the link capacity, then
the system slowly progresses in terms of a flow's view, and the
virtual time increases slowly. If there is only a handful of
backlogged flows, then the virtual time increases with a higher rate.
This behavior of the virtual time function prevents an unfair
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situation in which flows that entered late have relatively small FTs
thus receive services earlier for a considerable duration of time,
compared to existing flows.
F(p) represents the time that an ideal fluid system would complete
its service of packet p. In a real packetized FQ system, the packets
are served in the increasing order of the FT. The FT can be
calculated at the moment the packet arrives in the node, and the
value of FT is attached to the packet before the packet is stored in
the buffer. In general, there is a queue for each flow, the queues
are managed by FIFO manner, and the scheduler serves the queue having
the HoQ packet with the smallest FT. Alternatively, it is possible
to put all the packets in one queue and sort them, as packets are
enqueued or dequeued, according to the value of the FT. This
implementation requires a priority queue. The point of (1) is that,
in the worst case, when all the flows are active and the link is
fully used, a flow is served at an interval of L(p)/r. At the same
time, by using the work conserving scheduler, any excessive link
resources are shared among the flows. How fairly it is shared is the
main difference between various FQ schedulers.
In order to obtain F(p) in (1), the FT of the previous packet of the
flow, F(p-1), must be remembered. When a packet is received, it is
necessary to find out which flow it belongs to and find out the FT of
the latest packet of the corresponding flow. F(p-1) of this latest
packet is a value representative of the 'flow state'. The fact that
such state information must be memorized and read means a
considerable complexity at a core node managing millions of flows.
This is the main reason why such FQ schedulers are not actually used
on the Internet. In this document, we pay attention to the fact that
the fair service time interval information between packets is already
included in the FTs of the entrance node of a flow. Instead of
deriving a new FT at each core node, we will specify a method of
deriving the FT at downstream nodes by using the initial FT
calculated at the entrance node.
On the other hand, calculating V(t) also involves the complexity of
calculating the sum of r by tracking the flows currently being
serviced in real time. It is a complex calculation. Therefore,
instead of calculating V(t) accurately, methods for estimating it in
a simple way have been suggested. Among them, Virtual Clock (VC)
[ZHANG] uses the current time t instead of V(t) to determine the FT.
Self-clocked fair queuing [GOLESTANI] uses the FT of the recently
serviced packet of another flow instead of V(t). The document adopts
the VC's approach.
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Stiliadis showed that this series of FQ schedulers can belong to the
Packetized Rate Proportional Servers (PRPS) [STILIADIS-RPS]. For
example, PGPS and VC are PRPS, while self-clocked fair queuing is
not. It was proved that a network with all the nodes having one of
these PRPSs guarantee the E2E latency for flow. Moreover, any PRPS
scheduler yields the same E2E latency bound [STILIADIS-RPS].
5. Assumptions
In this document, we assume there are only two classes of traffic.
The high priority traffic requires guarantee on latency upper bounds.
All the other traffic is considered to be the low priority traffic,
and be completely preempted by the high priority traffic. High
priority traffic is our only concern.
All the flows conform to their traffic specification (TSpec)
parameters. In other words, with the maximum burst size Bi and the
arrival rate ai, the accumulated arrival from flow i in any arbitrary
time interval [t1, t2], t1 < t2, does not exceed Bi+(t2-t1)ai. An
actual allocated service rate to a flow, ri, can be larger than or
equal to the arrival rate of the flow. As it will be shown in (5)
that, by adjusting the service rate to a flow, the E2E latency bound
of the flow can be adjusted. Note that ri is used interchangeably
with the symbol r to denote the service rate of a flow. Total
allocated service rate to all the flows in a node does not exceed the
link capacity of the node. These assumptions make the resource
reservation and the admission control mandatory.
A node, or equivalently a server, means an output port module of a
switching device.
The entrance node for a flow is the node located at the edge of a
network, from which the flow enters into the network. A core node
for a flow is a node in the network, which is traversed by the flow
and is not the entrance node. Note that a single node can be both an
entrance node to a flow and a core node for another flow.
A packet is considered arrived or serviced; when its last bit has
arrived or left the node, respectively.
Propagation delays are neglected for the simplicity of
representation. However, it can be easily incorporated into the
equations presented in this document, if necessary. This issue will
be covered in Section 6.3.6.
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6. Work Conserving Stateless Core Fair Queuing (C-SCORE)
6.1. Framework
FQ schedulers utilize the concept of FT that is used as the service
order assigned to a packet. The packet with the minimum FT in a
buffer is served first.
As an example, the VC scheduler [ZHANG] defines the FT to be
F(p) = max{F(p-1), A(p)} + L(p)/r, (2)
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 completion 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.
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.
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In essence, (2) 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, which are necessary to 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. 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.
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) [C-SCORE], which can be compared to the existing
non-work conserving scheme [STOICA].
6.2. E2E Latency Bound
For C-SCORE to guarantee E2E latency bound, the dh(p) is RECOMMENDED
to be defined as in the following.
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dh(p) = SLh. (3)
The service latency of the flow at node h, denoted by SLh, is given
as follows.
SLh = Lh/Rh + L/r, (4)
where Lh is the observed maximum packet length in the node h over all
the flows, Rh is the link capacity of the node h, and L is the
maximum packet length in the flow.
The concept of the service latency was first introduced in the
Latency-rate server model [STILIADIS-LRS], which can be interpreted
as the worst delay the first packet of a new flow can experience in
the system.
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.
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 (3), then it can be proved that
Dh(p) <= (B-L)/r + SL0 + SL1 + ... + SLh, (5)
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 (5) 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.
6.3. Operational Procedure
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6.3.1. Metadata
As a packet arrives at a core node, it carries metadata F(h-1)(p),
d(h-1)(p), and L/r.
L/r should be kept in a packet in order to calculate dh(p) according
to (3) and (4).
Fh(p) and dh(p) are dynamic and thus need to be updated at every hop.
Fh(p) can be obtained by a summation of the metadata F(h-1)(p) and
d(h-1)(p).
dh(p) can be obtained by a summation of the metadata L/r and the node
specific parameter Lh/Rh.
They can be updated during the time interval between the packet
arrival to the switch (or router) and putting it into the queue in
the output port.
Alternatively, Fh(p) can be pre-calculated at node h-1 with
d(h-1)(p), which is the function of node h-1. In this case Fh(p) and
L/r are the only metadata necessary. In Section 6.3.3 and
Section 6.3.4, we follow this alternative approach.
The clear definition and format of metadata will be described in a
later version.
6.3.2. Network Configuration for latency guarantee
A source requests 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. 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 service rate should be chosen to be larger than or equal to the
arrival rate of the flow. The network reserves the links in the path
such that the sum of service rates to the flows does not exceed the
link capacity.
The detailed operational procedure for such admission and reservation
is out of scope of this document.
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6.3.3. Role of entrance node for generation and update of FT
It is assumed that the packet length of p, L(p), is written in the
packet header. Entrance node maintains the flow state, i.e. 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 (A0(p)).
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 the entrance node (d0(p)).
Upon receiving or generating packet p, it obtains F0(p) =
max{F0(p-1), A0(p)} + L(p)/r, and uses it as the FT in the entrance
node. If the queue is not empty then it puts p in a priority queue.
It also obtains F1(p) = F0(p) + L0/R0 + L/r before or during p is in
the queue. It writes F1(p) and L/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).
6.3.4. Role of core node for update of FT
A core node h collects the link information Lh/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) and L/r,
and uses Fh(p) as the FT value of the packet. It puts p in a
priority queue. It obtains F(h+1)(p) = Fh(p) + Lh/Rh + L/r and
updates the packet metadata Fh(p) with F(h+1)(p) before or during p
is in the queue.
6.3.5. Mitigation of complexity in 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.
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6.3.6. Compensation of time difference between nodes
As it has been stated in Section 5, we have assumed zero propagation
delays between nodes. In reality, there are time differences between
nodes, including the differences due to the propagation delays. This
time difference can be defined as the difference between the service
completion time of a packet measured at the upstream node and the
arrival time of the packet measured at the current node. In other
words,
td(h-1, h)(p) = Ah(p) - C(h-1)(p),
where td(h-1, h)(p) is the time difference between node h-1 and h,
and C(h-1)(p) is the service completion time measured at node h-1,
for packet p respectively.
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
td(h-1, h)(p) can be simplified to a constant value, td(h-1, h). In
this case the delay factor in (3) can be modified to be
dh(p) = SLh + td(h, h+1).
The E2E latency bound in (5) increases as much as the sum of
propagation delays from node 0 to h.
The time difference td(h-1, h) may 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 the
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 discrepancies and propagation delays, the
framework in this document does not need global time synchronization.
6.4. Characteristics
The framework in this document, C-SCORE, is a flow level, rate based,
work conserving, asynchronous, non-periodic, and in-time solution,
according to the taxonomy suggested by
[I-D.joung-detnet-taxonomy-dataplane].
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Its per hop latency dominant factor is maximum packet length divided
by service rate, independent of other flows' parameters. As such,
its most distinguishable strength is the flow isolation capability.
It can assign a fine tuned E2E latency bound to a flow, by
controlling the flow's own parameters such as the service rate. Once
the latency bound is assigned to the flow, then it remains almost the
same in spite of the network situation changes, such as other flows'
join and leave.
It is work conserving, thus enjoys the statistical multiplexing gain
without wasting bandwidth, which is the key to the Internet's
success. The consequence is a smaller average latency. The
observable maximum latency is also much smaller than the theoretical
latency bound. Note that, with a work conserving solution, observing
the theoretical latency bound is extremely difficult. It is because
the worst latency is an outcome of a combination of multiple rare
events, e.g. a maximum burst from a flow collides with the maximum
bursts from all other flows at every node. In contrast, non-work
conserving solutions make it common to observe their latency bounds.
It is rate based, thus the admission condition check process is
simple, which is dependent only on the service rates of flows. This
process aligns well with existing protocols.
Overall, C-SCORE suits large scale networks, at any utilization
level, with various types of flows join and leave dynamically.
7. IANA Considerations
There might be matters that require IANA considerations associated
with metadata. If necessary, relevant text will be added in a later
version.
8. Security Considerations
This section will be described later.
9. Acknowledgements
10. Contributor
11. References
11.1. Normative References
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[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>.
11.2. Informative References
[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.
[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.
[C-SCORE] Joung, J., Kwon, J., Ryoo, J., and T. Cheung, "Scalable
flow isolation with work conserving stateless core fair
queuing for deterministic networking", IEEE Access, vol.
11, pp. 105225 - 105247, doi:10.1109/ACCESS.2023.3318479,
2023.
[GOLESTANI]
Golestani, S. J., "A self-clocked fair queueing scheme for
broadband applications", in Proc. INFOCOM, vol. 1, pp.
636-646, doi: 10.1109/INFCOM.1994.337677, 1994.
[I-D.joung-detnet-taxonomy-dataplane]
Joung, J., Geng, X., Peng, S., and T. T. Eckert,
"Dataplane Enhancement Taxonomy", Work in Progress,
Internet-Draft, draft-joung-detnet-taxonomy-dataplane-01,
25 February 2024, <https://datatracker.ietf.org/doc/html/
draft-joung-detnet-taxonomy-dataplane-01>.
[KAUR] Kaur, J. and H.M. Vin, "Core-stateless guaranteed rate
scheduling algorithms", in Proc. INFOCOM, vol.3, pp.
1484-1492, 2001.
[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.
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[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.
[STILIADIS-RPS]
Stiliadis, D. and A. Anujan, "Rate-proportional servers: A
design methodology for fair queueing algorithms", IEEE/ACM
Trans. Networking, vol. 6, no. 2, pp. 164-174, 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.
[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
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Email: liupengyjy@chinamobile.com
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