Internet DRAFT - draft-finzi-priority-switching-scheduler
draft-finzi-priority-switching-scheduler
Internet Engineering Task Force Baker
Internet-Draft
Intended status: Informational Finzi
Expires: April 25, 2019 TTTech Computertechnik AG
Frances
ISAE-SUPAERO
Kuhn
CNES
Lochin
Mifdaoui
ISAE-SUPAERO
October 22, 2018
Priority Switching Scheduler
draft-finzi-priority-switching-scheduler-04
Abstract
We detail the implementation of a network rate scheduler based on
both a packet-based implementation of the generalized processor
sharing (GPS) and a strict priority policies. This credit based
scheduler called Priority Switching Scheduler (PSS), inherits from
the standard Strict Priority Scheduler (SP) but dynamically changes
the priority of one or several queues. Usual scheduling
architectures often combine rate schedulers with SP to implement
DiffServ service classes. Furthermore, usual implementations of rate
scheduler schemes (such as WRR, DRR, ...) do not allow to efficiently
guarantee the capacity dedicated to both AF and DF DiffServ classes
as they mostly provide soft bounds. This means excessive margin is
used to ensure the capacity requested and this impacts the number of
additional users that could be accepted in the network. PSS allows a
more predictable output rate per traffic class and is a one fit all
scheme allowing to enable both SP and rate scheduling policies within
a single algorithm.
Status of This Memo
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This Internet-Draft will expire on April 25, 2019.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1. Context and Motivation . . . . . . . . . . . . . . . . . 2
1.2. Definitions and Acronyms . . . . . . . . . . . . . . . . 3
1.3. Priority Switching Scheduler in a nutshell . . . . . . . 3
2. Priority Switching Scheduler . . . . . . . . . . . . . . . . 5
2.1. Specification . . . . . . . . . . . . . . . . . . . . . . 5
2.2. Implementation with three traffic classes and one
controlled queue . . . . . . . . . . . . . . . . . . . . 9
2.3. Implementation with n controlled queues . . . . . . . . . 10
3. Usecase: benefit of using PSS in a Diffserv core network . . 12
3.1. Motivation . . . . . . . . . . . . . . . . . . . . . . . 12
3.2. New service offered . . . . . . . . . . . . . . . . . . . 14
4. Security Considerations . . . . . . . . . . . . . . . . . . . 14
5. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 15
6. References . . . . . . . . . . . . . . . . . . . . . . . . . 15
6.1. Normative References . . . . . . . . . . . . . . . . . . 15
6.2. Informative References . . . . . . . . . . . . . . . . . 15
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 16
1. Introduction
1.1. Context and Motivation
To enable DiffServ traffic classes and share the capacity offered by
a link, many schedulers have been developed such as Strict Priority,
Weighted Fair Queuing, Weighted Round Robin or Deficit Round Robin.
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In the context of a core network router architecture aiming at
managing various kind of traffic classes, scheduling architectures
require to combine a Strict Priority (to handle real-time traffic)
and a rate scheduler (WFQ, WRR, ... to handle non-real time traffic)
as proposed in [RFC5865]. For all these solutions, the output rate
of a given queue often depends on the amount of traffic managed by
other queues. PSS aims at reducing the uncertainty of the output
rate of selected queues, we call them in the following controlled
queues. Additionally, compared to previous cited schemes, the
scheduling scheme proposed is simpler to implement as PSS allows to
both enable Strict Priority and Fair Queuing services; is more
flexible following the wide possibilities offered by this setting;
and does not require a virtual clock as for instance, WFQ.
1.2. Definitions and Acronyms
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
o AF: Assured Forwarding;
o BLS: Burst Limiting Shaper;
o DRR: Deficit Round Robin
o DF: Default Forwarding;
o EF: Expedited Forwarding;
o PSS: Priority Switching Scheduler;
o QoS: Quality-of-Service;
o FQ: Fair Queuing
o SP: Strict Priority
o WFQ: Weighted Fair Queuing
o WRR: Weighted Round Robin
1.3. Priority Switching Scheduler in a nutshell
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_____________________
| p_low[i] p_high[i] |
------|_____________________|
sets() | ^
_________|__ |
PSS controlled | | | | selects()
queue i ------------>| p[i]= v | |
| | credit[i]
. | . | ^
. | . | | updates()
. | . | |
non-active | |------------------> output
PSS queue j ------------>| p[j] | traffic
| |
. | . |
. | . |
. | . |
|____________|
Priority Scheduler
Figure 1: PSS in a nutshell
As illustrated in Figure 1, the principle of PSS is based on the use
of credit counters (detailed in the following) to change the priority
of one or several queues. Each controlled queue i is characterized
by a current priority state p[i], which can takes two priority
values: {p_high[i], p_low[i]} where p_high[i] the highest priority
value and p_low[i] the lowest. This idea follows a proposal made by
the TSN Task group named Burst Limiting Shaper [BLS]. For each
controlled queue i, each current priority p[i] changes between
p_low[i] and p_high[i] depending on the associated credit counter
credit[i]. Then a Priority Scheduler is used for the dequeuing
process, i.e., among the queues with available traffic, the first
packet of the queue with the highest priority is dequeued.
The main idea is that changing the priorities adds fairness to the
Priority Scheduler. Depending on the credit counter parameters, the
amount of capacity available to a controlled queue is bounded between
a minimum and a maximum value. Consequently, good parameterization
is very important to prevent starvation of lower priority queues.
The service obtained for the controlled queue with the switching
priority is more predictable and corresponds to the minimum between a
desired capacity and the residual capacity left by higher priorities.
The impact of the input traffic sporadicity from higher classes is
thus transfered to non-active PSS queues with a lower priority.
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Finally, PSS offers much flexibility as both controlled queues with a
guaranteed capacity (when two priorities are set) and queues
scheduled with a simple Priority Scheduler (when only one priority is
set) can conjointly be enabled.
2. Priority Switching Scheduler
2.1. Specification
For the sake of clarity and to ease the understanding of the PSS
algorithm, we consider the case where only one queue is a controlled
queue. This corresponds to three traffic classes EF, AF and DF where
AF is the controlled queue as shown in Figure Figure 2.
queues priority ___
________ | \
EF--->|________|-----{1}----+ \
| \
________ | \
AF--->|________|-----{2,4}--+ PSS --->
| /
________ | /
DF--->|________|-----{3}----+ /
|___/
Figure 2: PSS with three traffic classes
As previously explained, the PSS algorithm defines for the controlled
queue a low priority denoted p_low, and a high priority denoted
p_high associated to a credit counter denoted credit, which manages
the priority switching. Considering Figure 2, the priority p[AF] of
the controlled queue AF will be switched between two priorities where
p_high[AF] = 2 and p_low[AF] = 4. The generalisation of PSS
algorithm to n controlled queues is given in Section 2.3.
Then, each credit counter is defined by:
o a minimum level: 0;
o a maximum level: LM;
o a resume level: LR such as 0 <= LR < LR;
o a reserved capacity: BW;
o an idle slope: I_idle = C * BW, where C is the link output
capacity;
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o a sending slope: I_send = C - I_idle;
The available capacity (denoted C) is mostly impacted by the
guaranteed capacity BW. Hence, BW should be set to the desired
capacity plus a margin taking into account the additional packet due
to non-preemption as explained below:
the value of LM can negatively impact on the guaranteed available
capacity. The maximum level determines the size of the maximum
sending windows, i.e, the maximum uninterrupted transmission time of
the controlled queue packets before a priority switching. The impact
of the non-preemption is as a function of the value of LM. The
smaller the LM, the larger the impact of the non-preemption is. For
example, if the number of packets varies between 4 and 5, the
variation of the output traffic is around 25% (i.e. going from 4 to 5
corresponds to a 25% increase). If the number of packets sent varies
between 50 and 51, the variation of the output traffic is around 2%.
The credit allows to keep track of the packet transmissions.
However, keeping track the transmission raises an issue in two cases:
when the credit is saturated at LM or at 0. In both cases, packets
are transmitted without gained or consumed credit. Nevertheless, the
resume level can be used to decrease the times when the credit is
saturated at 0. If the resume level LR is 0, then as soon as the
credit reaches 0, the priority is switched and the credit saturates
at 0 due to the non-preemption of the current packet. On the
contrary, if LR > 0, then during the transmission of the non-
preempted packet, the credit keeps on decreasing before reaching 0 as
illustrated in Figure 3.
Hence, the proposed value for LR is Lmax * BW, with Lmax the maximum
packet size of the controlled queue. With this value, there is no
credit saturation at 0 due to non-preemption.
A similar parameter setting is described in [Globecom17], to
transform WRR parameter into PSS parameters, also in the case of a
three classes DiffServ architecture.
The priority change depends on the credit counter as follows:
o initially, the credit counter starts at 0;
o the change of priority p[i] of controlled queue i occurs in two
cases:
* if p[i] is currently set to p_high[i] and credit[i] reaches LM;
* if p[i] is currently set to p_low[i] and credit[i] reaches LR;
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o when a packet of the controlled queue is transmitted, the credit
increases (is consumed) with a rate I_send, else the credit
decreases (is gained) with a rate I_idle;
o when the credit reaches LM, it remains at this level until the end
of the transmission of the current packet (if any);
o when the credit reaches LR and the transmission of the current
packet is finished, in the abscence of new packets to transmit in
the controlled queue, it keeps decreasing at the rate I_idle until
it reaches 0. Finally, the credit remains to 0 until the start of
the transmission of a new packet.
Figure 3 and Figure 4 give two examples of credit and priority
changes of a given queue. First, Figure 3 gives an example when the
controlled queue sends its traffic continuously until the priority
changes (this traffic is represented with @ below the x-axis of this
figure). Then, the credit reaches LM and the last packet is
transmitted although the priority have changed. Other traffic is
thus sent (represented by o) uninterruptedly until the priority
changes back. Figure 4 illustrates a more complex behaviour. First,
this figure shows when a packet with a priority higher than p_high[i]
is available, this packet is sent before the traffic of queue i.
Secondly, when no traffic with a priority lower than p_low[i] is
available, then traffic of queue i can be sent. This highlights the
non-blocking nature of PSS and that p[i] = p_high[i] (resp. p[i] =
p_low[i]) does not necessarily mean that traffic of queue i is being
sent (resp. not being sent).
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^ credit
| | |
| p_high | p_low | p_high
LM |- - - - -++++++- - - - - - - |- - - -+++
| +| |+ | +
|I_send + | | + I_idle | +
| + | | + | +
| + | | + | +
| + | | + | +
| + | | + | +
LR | + | | + |+
0 |-+- - - -|- - |- - - - - - - +- - - - - >
| | time
@@@@@@@@@@@@@@@@oooooooooooooo@@@@@@@@@@
@ controlled queue traffic
o other traffic
Figure 3: First example of queue credit evolution and priority
switching.
^ credit
| |
| p_high | p_low
LM + - - - - - - - - - - - -++++ - - - - - - -+
| +| |+ +
| ++ + | | + +
| + | + + | | + +
| ++ + | + | | +
| +| + + | | | | |
| + | + | | | | |
LR +--+--|-----|----|---|---|--|------|-------
0 +-+- -| - - |- - |- -|- -|- |- - - |- - - - >
| | | | | | time
@@@@@@oooooo@@@@@oooo@@@@@@@@oooooo@@@@@@@
@ controlled queue traffic
o other traffic
Figure 4: Second example of queue credit evolution and priority
switching.
Finally, for the dequeuing process, a Priority Scheduler selects the
appropriate packet using the current priority values. In other
words, among the queues with packets enqueued, the first packet of
the queue with the highest priority is dequeued (usual principle of
SP).
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2.2. Implementation with three traffic classes and one controlled queue
The new dequeuing algorithm is presented in the PSS Algorithm in
Figure 5 and consists in a modification of the standard SP. The
credit of the controlled queue and the dequeuing timer denoted
timerDQ are initialized to zero. The initial priority is set to the
highest value p_high. First, we compute the difference between the
current time and the time stored in timerDQ (line #3). The duration
dtime represents the time elapsed since the last credit update,
during which no packet from the controlled queue was sent, we call
this the idle time. Then, if dtime > 0, the credit is updated by
removing the credit gained during the idle time that just occurred
(lines #4 and #5). Next, timerDQ is set to the current time to keep
track of the last time the credit was updated (line #6). If the
credit reaches LR, the priority changes to its high value (lines #7
and #8). Then, with the updated priorities, SP algorithm performs as
usual: each queue is checked for dequeuing, highest priority first
(lines #12 and #13). When the queue selected is the controlled
queue, the credit expected to be consumed is added to the credit
variable (line #16). The time taken for the packet to be dequeued is
added to the variable timerDQ (line #17) so the transmission time of
the packet will not be taken into account in the idle time dtime
(line #3). If the credit reaches LM, the priority changes to its low
value (lines #18 and #19). Finally, the packet is dequeued (line
#22).
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Inputs: credit, timerDQ, C, LM, LR, BW, p_high, p_low
1 currentTime = getCurrentTime()
3 dtime = currentTime - timerDQ
4 if dtime > 0 then:
5 credit = max(credit - dtime * C * BW, 0)
6 timerDQ = currentTime
7 if credit < LR and p = p_low then:
8 p = p_high
9 end if
10 end if
11 end for
12 for each priority level, highest first do:
13 if length(queue[i]) > 0 then:
15 if queue[i] is the controlled queue then:
16 credit =
min(LM, credit + size(head(queue[i])) * (1 - BW))
17 timerDQ = currentTime + size(head(queue[i]))/C
18 if credit >= LM and p = p_high then:
19 p = p_low
20 end if
21 end if
22 dequeue(head(queue[i]))
23 break
24 end if
25 end for
Figure 5: PSS algorithm
PSS algorithm implements the following functions:
o getCurrentTime() uses a timer to return the current time;
o length(q) returns the length of the queue q;
o head(q) returns the first packet of queue q;
o size(f) returns the size of packet f;
o dequeue(f) activates the dequeing event of packet f.
2.3. Implementation with n controlled queues
The algorithm can be updated to support n controlled queues. In this
context, the credits of each queue i must be stored in the table
creditList[i]. Each controlled queue i has its own dequeuing timer
stored in the table timerDQList[i]. Likewise for each controlled
queue, LM[i], LR[i], BW[i], p_low[i] and p_high[i] are respectively
stored in LMList[i], LRList[i], BWList[i], p_lowList[i] and
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p_highList[i]. A controlled queue i is characterized by p_lowList[i]
> p_highList[i] (as priority 0 is the highest priority for SP). The
current priority of a controlled queue is stored in p[i]. Each
controlled queue must have distinct priorities.
As an example, Figure Figure 6 extends Figure 2 to n controlled
queues.
queues prio ___
________ | \
Admitted EF--->|________|-----{1}----+ \
| \
________ | \
Unadmitted EF--->|________|-----{2}----+ \
| \
________ | \
AF1-->|________|-----{3,6}--+ PSS --->
| /
________ | /
AF2-->|________|-----{4,7}--+ /
| /
________ | /
DF--->|________|-----{5}----+ /
|___/
Figure 6: PSS with three traffic classes
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Inputs: creditList[], timerDQList[], C, LMList[], LRList[],
BWList[],p_highList[], p_lowList[]
1 for each queue i with p_highList[i] < p_lowList[i] do:
2 currentTime = getCurrentTime()
3 dtime = currentTime - timerDQList[i]
4 if dtime >0 then:
5 creditList[i] =
max(creditList[i] - dtime * C * BWList[i], 0)
6 timerDQList[i] = currentTime
7 if credit[i] < LRList[i] and p[i] = p_lowList[i] then:
8 p[i] = p_highList[i]
9 end if
10 end if
11 end for
12 for each priority level pl, highest first do:
13 if length(queue(pl)) > 0 then:
14 i = queue(pl)
15 if p_highList[i] < p_lowList[i] then:
16 creditList[i] =
min(LMList[i],
creditList[i] + size(head(i)) * (1 - BWList[i]))
17 timerDQList[i] = currentTime + size(head(i))/C
18 if creditList[i] >= LMList[i]
and p[i] = p_highList[i] then:
19 p[i] = p_lowList[i]
20 end if
21 end if
22 dequeue(head(i))
23 break
24 end if
25 end for
Figure 7: PSS algorithm
The general PSS algorithm also implements the following function:
o queue(pl) returns the queue i associated to priority pl.
3. Usecase: benefit of using PSS in a Diffserv core network
3.1. Motivation
The DiffServ architecture defined in [RFC4594] and [RFC2475] proposes
a scalable mean to deliver IP quality of service (QoS) based on
handling traffic aggregates. This architecture follows the
philosophy that complexity should be delegated to the network edges
while simple functionalities should be located in the core network.
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Thus, core devices only perform differentiated aggregate treatments
based on the marking set by edge devices.
Keeping aside policing mechanisms that might enable edge devices in
this architecture, a DiffServ stateless core network is often used to
differentiate time-constrained UDP traffic (e.g. VoIP or VoD) and
TCP bulk data transfer from all the remaining best-effort (BE)
traffic called default traffic (DF). The Expedited Forwarding (EF)
class is used to carry UDP traffic coming from time-constrained
applications (VoIP, Command/Control, ...); the Assured Forwarding
(AF) class deals with elastic traffic as defined in [RFC4594] (data
transfer, updating process, ...) while all other remaining traffic is
classified inside the default (DF) best-effort class.
The first and best service is provided to EF as the priority
scheduler attributes the highest priority to this class. The second
service is called assured service and is built on top of the AF class
where elastic traffic such as TCP traffic, is intended to achieve a
minimum level of throughput. Usually, the minimum assured throughput
is given according to a negotiated profile with the client. The
throughput increases as long as there are available resources and
decreases when congestion occurs. As a matter of fact, a simple
priority scheduler is insufficient to implement the AF service. TCP
traffic increases until reaching the capacity of the bottleneck due
to its opportunistic nature of fetching the full remaining capacity.
In particular, this behaviour could lead to starve the DF class.
To prevent a starvation and ensure to both DF and AF a minimum
service rate, the router architecture proposed in [RFC5865] uses a
rate scheduler between AF and DF classes to share the residual
capacity left by the EF class. Nevertheless, one drawback of using a
rate scheduler is the high impact of EF traffic on AF and DF.
Indeed, the residual capacity shared by AF and DF classes is directly
impacted by the EF traffic variation. As a consequence, the AF and
DF class services are difficult to predict in terms of available
capacity and latency. To overcome these limitations and make AF
service more predictable, we propose here to use the newly defined
Priority Switching Scheduler (PSS).
Figure 8 shows an example of the Data Plane Priority core network
router presented in [RFC5865] modified with a PSS. The EF queues
have the highest priorities to offer the best service to real-time
traffic. The priority changes set the AF priorities either higher
(3,4) or lower (6,7) than CS0 (5), leading to capacity sharing (CS0
refers to Class Selector codepoints 0 and is usually refered to DF as
explained in [RFC7657]). Another example with only 3 queues is
described in [Globecom17]. Thank to the increase predictability, for
the same minimum guaranteed rate, the PSS reserves a lower percentage
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of the capacity than a rate scheduler. This leaves more remaining
capacity that can be guaranteed to other users.
prio ___
| \
Admitted EF------{p[AEF] = 1}--------+ \
| \
| \
Unadmitted EF----{p[UEF] = 2}--------+ \
| \
| \
AF1--{p_high[AF1]=3, p_low[AF1]= 6}--+ PSS --->
| /
| /
AF2--{p_high[AF2]=4, p_low[AF2]= 7}--+ /
| /
| /
CS0------------{p[CS0] = 5}----------+ /
|___/
Figure 8: PSS applied to Data Plane Priority (we borrow the syntax
from RCF5865)
3.2. New service offered
The new service we seek to obtain is:
o for EF, the full capacity of the output link;
o for AF the minimum between a desired capacity and the residual
capacity left by EF;
o for DF (CS0), the residual capacity left by EF and AF.
As a result, the AF class has a more predictable available capacity,
while the unpredictability is reported on the DF class. With good
parametrization, both classes also have a minimum rate ensured.
Parameterization and simulations results concerning the use of a
similar scheme for core network scheduling are available in
[Globecom17]
4. Security Considerations
There are no specific security exposure with PSS that would extend
those inherent in default FIFO queuing or in static priority
scheduling systems. However, following the DiffServ usecase proposed
in this memo and in particular the illustration of the integration of
PSS as a possible implementation of the architecture proposed in
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[RFC5865], most of the security considerations from [RFC5865] and
more generally from the differentiated services architecture
described in [RFC2475] still hold.
5. Acknowledgements
This document was the result of collaboration and discussion among a
large number of people. In particular the authors wish to thank
David Black, Ruediger Geib, Vincent Roca for reviewing this draft and
Victor Perrier for the TUN/TAP implementation of PSS. At last but
not least, a very special thanks to Fred Baker for his help.
6. References
6.1. Normative References
[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>.
6.2. Informative References
[BLS] Gotz, F-J., "Traffic Shaper for Control Data Traffic
(CDT)", IEEE 802 AVB Meeting , 2012.
[Globecom17]
Finzi, A., Lochin, E., Mifdaoui, A., and F. Frances,
"Improving RFC5865 Core Network Scheduling with a Burst
Limiting Shaper", Globecom , 2017,
<http://oatao.univ-toulouse.fr/18448/>.
[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>.
[RFC4594] Babiarz, J., Chan, K., and F. Baker, "Configuration
Guidelines for DiffServ Service Classes", RFC 4594,
DOI 10.17487/RFC4594, August 2006,
<https://www.rfc-editor.org/info/rfc4594>.
[RFC5865] Baker, F., Polk, J., and M. Dolly, "A Differentiated
Services Code Point (DSCP) for Capacity-Admitted Traffic",
RFC 5865, DOI 10.17487/RFC5865, May 2010,
<https://www.rfc-editor.org/info/rfc5865>.
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[RFC7657] Black, D., Ed. and P. Jones, "Differentiated Services
(Diffserv) and Real-Time Communication", RFC 7657,
DOI 10.17487/RFC7657, November 2015,
<https://www.rfc-editor.org/info/rfc7657>.
Authors' Addresses
Fred Baker
Santa Barbara, California 93117
USA
Email: FredBaker.IETF@gmail.com
Anais Finzi
TTTech Computertechnik AG
Schoenbrunner Strasse 7
Vienna 1040
Austria
Phone: 0043158534340
Email: anais.finzi@tttech.com
Fabrice Frances
ISAE-SUPAERO
10 Avenue Edouard Belin
Toulouse 31400
France
Email: fabrice.frances@isae-supaero.fr
Nicolas Kuhn
CNES
18 Avenue Edouard Belin
Toulouse 31400
France
Email: nicolas.kuhn@cnes.fr
Baker, et al. Expires April 25, 2019 [Page 16]
Internet-Draft Priority Switching Scheduler October 2018
Emmanuel Lochin
ISAE-SUPAERO
10 Avenue Edouard Belin
Toulouse 31400
France
Phone: 0033561338485
Email: emmanuel.lochin@isae-supaero.fr
Ahlem Mifdaoui
ISAE-SUPAERO
10 Avenue Edouard Belin
Toulouse 31400
France
Email: ahlem.mifdaoui@isae-supaero.fr
Baker, et al. Expires April 25, 2019 [Page 17]