draft-ietf-teas-native-ip-scenarios-01.txt   draft-ietf-teas-native-ip-scenarios-02.txt 
TEAS Working Group A. Wang TEAS Working Group A. Wang
Internet-Draft China Telecom Internet-Draft China Telecom
Intended status: Experimental X. Huang Intended status: Experimental X. Huang
Expires: December 28, 2018 C. Kou Expires: April 24, 2019 C. Kou
BUPT BUPT
Z. Li Z. Li
China Mobile China Mobile
L. Huang
P. Mi P. Mi
Huawei Technologies Huawei Technologies
June 26, 2018 October 21, 2018
CCDR Scenario, Simulation and Suggestion Scenario, Simulation and Suggestion of PCE in Native IP Network
draft-ietf-teas-native-ip-scenarios-01 draft-ietf-teas-native-ip-scenarios-02
Abstract Abstract
This document describes the scenarios, simulation and suggestions for This document describes the scenarios, simulation and suggestions for
the "Centrally Control Dynamic Routing (CCDR)" architecture, which PCE in native IP network, which integrates the merit of distributed
integrates the merit of traditional distributed protocols (IGP/BGP), protocols (IGP/BGP), and the power of centrally control technologies
and the power of centrally control technologies (PCE/SDN) to provide (PCE/SDN) to provide one feasible traffic engineering solution in
one feasible traffic engineering solution in various complex various complex scenarios for the service provider.
scenarios for the service provider.
Traditional MPLS-TE solution is mainly used in static network
planning scenario and is difficult to meet the QoS assurance
requirements in real-time traffic network. With the emerge of SDN
concept and related technologies, it is possible to simplify the
complexity of distributed control protocol, utilize the global view
of network condition, give more efficient solution for traffic
engineering in various complex scenarios.
Status of This Memo Status of This Memo
This Internet-Draft is submitted in full conformance with the This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79. provisions of BCP 78 and BCP 79.
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This Internet-Draft will expire on December 28, 2018.
This Internet-Draft will expire on April 24, 2019.
Copyright Notice Copyright Notice
Copyright (c) 2018 IETF Trust and the persons identified as the Copyright (c) 2018 IETF Trust and the persons identified as the
document authors. All rights reserved. document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents Provisions Relating to IETF Documents
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publication of this document. Please review these documents publication of this document. Please review these documents
skipping to change at page 2, line 27 skipping to change at page 2, line 17
include Simplified BSD License text as described in Section 4.e of include Simplified BSD License text as described in Section 4.e of
the Trust Legal Provisions and are provided without warranty as the Trust Legal Provisions and are provided without warranty as
described in the Simplified BSD License. described in the Simplified BSD License.
Table of Contents Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Conventions used in this document . . . . . . . . . . . . . . 3 2. Conventions used in this document . . . . . . . . . . . . . . 3
3. CCDR Scenarios. . . . . . . . . . . . . . . . . . . . . . . . 3 3. CCDR Scenarios. . . . . . . . . . . . . . . . . . . . . . . . 3
3.1. Qos Assurance for Hybrid Cloud-based Application. . . . . 3 3.1. Qos Assurance for Hybrid Cloud-based Application. . . . . 3
3.2. Increase link utilization based on tidal phenomena. . . . 4 3.2. Link Utilization Maximization . . . . . . . . . . . . . . 4
3.3. Traffic engineering for IDC/MAN asymmetric link . . . . . 5 3.3. Traffic Engineering for Multi-Domain . . . . . . . . . . 5
3.4. Network temporal congestion elimination. . . . . . . . . 6 3.4. Network temporal congestion elimination. . . . . . . . . 6
4. CCDR Simulation. . . . . . . . . . . . . . . . . . . . . . . 6 4. CCDR Simulation. . . . . . . . . . . . . . . . . . . . . . . 6
4.1. Topology Simulation . . . . . . . . . . . . . . . . . . . 6 4.1. Topology Simulation . . . . . . . . . . . . . . . . . . . 6
4.2. Traffic Matrix Simulation. . . . . . . . . . . . . . . . 7 4.2. Traffic Matrix Simulation. . . . . . . . . . . . . . . . 7
4.3. CCDR End-to-End Path Optimization . . . . . . . . . . . . 7 4.3. CCDR End-to-End Path Optimization . . . . . . . . . . . . 7
4.4. Network temporal congestion elimination . . . . . . . . . 9 4.4. Network Temporal Congestion Elimination . . . . . . . . . 9
5. CCDR Deployment Consideration. . . . . . . . . . . . . . . . 10 5. CCDR Deployment Consideration. . . . . . . . . . . . . . . . 10
6. Security Considerations . . . . . . . . . . . . . . . . . . . 11 6. Security Considerations . . . . . . . . . . . . . . . . . . . 11
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 11 7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 11
8. Normative References . . . . . . . . . . . . . . . . . . . . 11 8. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 11
9. Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . 11
10. Normative References . . . . . . . . . . . . . . . . . . . . 11
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 12 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 12
1. Introduction 1. Introduction
Internet network is composed mainly tens of thousands of routers that Service provider network is composed mainly thousands of routers that
run distributed protocol to exchange the reachability information run distributed protocol to exchange the reachability information
between them. The path for the destination network is mainly between them. The path for the destination network is mainly
calculated and controlled by the traditional IGP protocols. These calculated and controlled by the IGP/BGP protocols. These
distributed protocols are robust enough to support the current distributed protocols are robust enough to support the current
evolution of Internet but has some difficulties when the application evolution of Internet but have some difficulties when application
requires the end-to-end QoS performance, or the service provider requires the end-to-end QoS performance, or in the situation that the
wants to maximize the links utilization within their network. service provider wants to maximize the links utilization within their
MPLS-TE technology is one perfect solution for the finely planned
network but it will put heavy burden on the router when we use it to
solve the dynamic QoS assurance requirements within real time traffic
network. network.
SR(Segment Routing) is another prominent solution that integrates MPLS-TE technology is one solution for finely planned network but it
some merits of traditional distributed protocol and the advantages of will put heavy burden on the routers when we use it to meet the
centrally control mode, but it requires the underlying network, dynamic QoS assurance requirements within real time traffic network.
especially the provider edge router to do label push and pop action
in-depth, and need some complex solutions for co-exist with the Non-
SR network. Finally, it can only maneuver the end-to-end path for
MPLS and IPv6 traffic via different mechanisms.
The advantage of MPLS is mainly for traffic isolation, such as the SR(Segment Routing) is another solution that integrates some merits
L2/L3 VPN service deployments, but most of the current application of distributed protocol and the advantages of centrally control mode,
requirements are only for high performances end-to-end QoS assurance. but it requires the underlying network, especially the provider edge
Without the help of centrally control architecture, the service router to do label push and pop action in-depth, and need complex
provider almost can't make such SLA guarantees upon the real time mechanics for co-exist with the Non-SR network. Aditionally, it can
traffic situation. only maneuver the end-to-end path for MPLS and IPv6 traffic via
different mechanisms.
This draft gives some scenarios that the centrally control dynamic This draft describes scenarios that the centrally control dynamic
routing (CCDR) architecture can easily solve, without adding more routing (CCDR) framework can easily solve, without adding more extra
extra burdening on the router. It also gives the PCE algorithm burdening on the router. It also gives the path optimization
results under the similar topology, traffic pattern and network size simulation results to illustrate the applicability of CCDR framework.
to illustrate the applicability of CCDR architecture. Finally, it Finally, it gives some suggestions for the implementation and
gives some suggestions for the implementation and deployment of CCDR. deployment of CCDR.
2. Conventions used in this document 2. Conventions used in this document
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119]. document are to be interpreted as described in RFC 2119 [RFC2119].
3. CCDR Scenarios. 3. CCDR Scenarios.
The following sections describe some scenarios that the CCDR The following sections describe some scenarios that the CCDR
architecture is suitable for deployment. framework is suitable for deployment.
3.1. Qos Assurance for Hybrid Cloud-based Application. 3.1. Qos Assurance for Hybrid Cloud-based Application.
With the emerge of cloud computing technologies, enterprises are With the emerge of cloud computing technologies, enterprises are
putting more and more services on the public oriented service putting more and more services on the public oriented cloud
infrastructure, but keep still some core services within their environment, but keep core business within their private cloud. The
network. The bandwidth requirements between the private cloud and communication between the private and public cloud will span the WAN
the public cloud are occasionally and the background traffic between network. The bandwidth requirements between them are variable and
these two sites varied from time to time. Enterprise cloud the background traffic between these two sites changes from time to
applications just want to invoke the network capabilities to make the time. Enterprise applications just want to exploit the network
end-to-end QoS assurance on demand. Otherwise, the traffic should be capabilities to assure the end-to-end QoS performance on demand.
controlled by the distributed protocol.
CCDR, which integrates the merits of distributed protocol and the CCDR, which integrates the merits of distributed protocol and the
power of centrally control, is suitable for this scenario. The power of centrally control, is suitable for this scenario. The
possible solution architecture is illustrated below: possible solution framework is illustrated below:
+------------------------+ +------------------------+
| Cloud Based Application| | Cloud Based Application|
+------------------------+ +------------------------+
| |
+-----------+ +-----------+
| PCE | | PCE |
+-----------+ +-----------+
| |
| |
//--------------\\ //--------------\\
///// \\\\\ ///// \\\\\
Private Cloud Site || Distributed |Public Cloud Site Private Cloud Site || Distributed |Public Cloud Site
| Control Network | | Control Network |
\\\\\ ///// \\\\\ /////
\\--------------// \\--------------//
Fig.1 Hybrid Cloud Communication Scenario Fig.1 Hybrid Cloud Communication Scenario
By default, the traffic path between the private cloud site and By default, the traffic path between the private and public cloud
public cloud site will be determined by the distributed control site will be determined by the distributed control network. When
network. When some applications require the end-to-end QoS applications require the end-to-end QoS assurance, it can send these
assurance, it can send these requirements to PCE, let PCE compute one requirements to PCE, let PCE compute one e2e path which is based on
e2e path which is based on the underlying network topology and the the underlying network topology and the real traffic information, to
real traffic information, to accommodate the application's QoS accommodate the application's QoS requirements. The proposed
requirements. The proposed solution can refer the draft solution can refer the draft [I-D.ietf-teas-pce-native-ip].
[I-D.ietf-teas-pce-native-ip]. Section 4 describes the detail Section 4 describes the detail simulation process and the result.
simulation process and the results.
3.2. Increase link utilization based on tidal phenomena. 3.2. Link Utilization Maximization
Currently, the network topology within MAN is generally in star mode Network topology within MAN is generally in star mode as illustrated
as illustrated in Fig.2, with the different devices connect different in Fig.2, with different devices connect different customer types.
customer types. The traffic pattern of these customers demonstrates The traffic from these customers is often in tidal pattern that the
some tidal phenomena that the links between the CR/BRAS and CR/SR links between the CR/BRAS and CR/SR will experience congestion in
will experience congestion in different periods because the different periods, because the subscribers under BRAS often use the
subscribers under BRAS often use the network at night and the network at night and the dedicated line users under SR often use the
dedicated line users under SR often use the network during the network during the daytime. The uplink between BRAS/SR and CR must
daytime. The uplink between BRAS/SR and CR must satisfy the maximum satisfy the maximum traffic volume between them respectively and this
traffic pattern between them and this causes the links causes these links often in underutilization situation.
underutilization.
+--------+ +--------+
| CR | | CR |
+----|---+ +----|---+
| |
--------|--------|-------| --------|--------|-------|
| | | | | | | |
+--|-+ +-|- +--|-+ +-|+ +--|-+ +-|- +--|-+ +-|+
|BRAS| |SR| |BRAS| |SR| |BRAS| |SR| |BRAS| |SR|
+----+ +--+ +----+ +--+ +----+ +--+ +----+ +--+
Fig.2 STAR-style network topology within MAN Fig.2 Star-mode Network Topology within MAN
If we can consider link the BRAS/SR with local loop, and control the If we consider to connect the BRAS/SR with local link loop (which is
MAN with the CCDR architecture, we can exploit the tidal phenomena more cheaper), and control the MAN with the CCDR framework, we can
between BRAS/CR and SR/CR links, increase the efficiency of them. exploit the tidal phenomena between BRAS/CR and SR/CR links, maximize
the links (which is more expensive) utilization of them .
+-------+ +-------+
----- PCE | ----- PCE |
| +-------+ | +-------+
+----|---+ +----|---+
| CR | | CR |
+----|---+ +----|---+
| |
--------|--------|-------| --------|--------|-------|
| | | | | | | |
+--|-+ +-|- +--|-+ +-|+ +--|-+ +-|- +--|-+ +-|+
|BRAS-----SR| |BRAS-----SR| |BRAS-----SR| |BRAS-----SR|
+----+ +--+ +----+ +--+ +----+ +--+ +----+ +--+
Fig.3 Increase the link utilization via CCDR Fig.3 Link Utilization Maximization via CCDR
3.3. Traffic engineering for IDC/MAN asymmetric link 3.3. Traffic Engineering for Multi-Domain
The operator's networks are often comprised by tens of different Operator's networks are often comprised by different domains,
domains, interconnected with each other, form very complex topology interconnected with each other, form very complex topology that
that illustrated in Fig.4. Due to the traffic pattern to/from MAN illustrated in Fig.4. Due to the traffic pattern to/from MAN and
and IDC, the links between them are often in asymmetric style. It is IDC, the utilization of links between them are often in asymmetric.
almost impossible to balance the utilization of these links via the It is almost impossible to balance the utilization of these links via
distributed protocol, but this unbalance phenomenon can be overcome the distributed protocol, but this unbalance phenomenon can be
via the CCDR architecture. overcome via the CCDR framework.
+---+ +---+ +---+ +---+
|MAN|-----------------IDC| |MAN|-----------------IDC|
+-|-| | +-|-+ +-|-| | +-|-+
| ---------| | | ---------| |
------|BackBone|------ ------|BackBone|------
| ----|----| | | ----|----| |
| | | | | |
+-|-- | ----+ +-|-- | ----+
|IDC|----------------|MAN| |IDC|----------------|MAN|
+---| |---+ +---| |---+
Fig.4 TE within Complex Multi-Domain topology Fig.4 Traffic Engineering for Complex Multi-Domain Topology
Solution for this scenario requires the gather of NetFlow
information, analysis the source/destination AS of them and determine
which pair is the main cause of the congested link. After this, the
operator can use the multi eBGP sessions described in
[I-D.ietf-teas-pce-native-ip]to schedule the traffic among different
domains.
3.4. Network temporal congestion elimination. 3.4. Network temporal congestion elimination.
In more general situation, there are often temporal congestion In more general situation, there are often temporal congestions
periods within part of the service provider's network. Such within the service provider's network. Such congestion phenomena
congestion phenomena will appear repeatedly and if the service often appear repeatedly and if the service provider has some methods
provider has some methods to mitigate it, it will certainly increase to mitigate it, it will certainly increase the degree of satisfaction
the satisfaction degree of their customer. CCDR is also suitable for for their customers. CCDR is also suitable for such scenario in such
such scenario that the traditional distributed protocol will process manner that the distributed protocol process most of the traffic
most of the traffic forwarding and the controller will schedule some forwarding and the controller schedule some traffic out of the
traffic out of the congestion links to lower the utilization of them. congestion links to lower the utilization of them. Section 4
Section 4 describes the simulation process and results about such describes the simulation process and results about such scenario.
scenario.
4. CCDR Simulation. 4. CCDR Simulation.
The following sections describe the topology, traffic matrix, end-to- The following sections describe the topology, traffic matrix, end-to-
end path optimization and congestion elimination in CCDR simulation. end path optimization and congestion elimination in CCDR applied
scenarios.
4.1. Topology Simulation 4.1. Topology Simulation
The network topology mainly contains nodes and links information. The network topology mainly contains nodes and links information.
Nodes used in simulation have two types: core nodes and edge nodes. Nodes used in simulation have two types: core node and edge node.
The core nodes are fully linked to each other. The edge nodes are The core nodes are fully linked to each other. The edge nodes are
connected only with some of the core nodes. Fig.5 is a topology connected only with some of the core nodes. Fig.5 is a topology
example of 4 core nodes and 5 edge nodes. In CCDR simulation, 100 example of 4 core nodes and 5 edge nodes. In CCDR simulation, 100
core nodes and 400 edge nodes are generated. core nodes and 400 edge nodes are generated.
+----+ +----+
/|Edge|\ /|Edge|\
| +----+ | | +----+ |
| | | |
| | | |
skipping to change at page 7, line 26 skipping to change at page 7, line 26
+----+ | / \ | | +----+ | / \ | |
\ | / \ | | \ | / \ | |
+----+ +----+ +----+ | +----+ +----+ +----+ |
|Edge|----|Core|-----|Core| | |Edge|----|Core|-----|Core| |
+----+ +----+ +----+ | +----+ +----+ +----+ |
| | | | | |
| +------\ +----+ | +------\ +----+
| ---|Edge| | ---|Edge|
+-----------------/ +----+ +-----------------/ +----+
Fig.5 Topology of simulation Fig.5 Topology of Simulation
The number of links connecting one edge node to the set of core nodes The number of links connecting one edge node to the set of core nodes
is randomly between 2 to 30, and the total number of links is more is randomly between 2 to 30, and the total number of links is more
than 20000. Each link has its congestion threshold. than 20000. Each link has its congestion threshold.
4.2. Traffic Matrix Simulation. 4.2. Traffic Matrix Simulation.
The traffic matrix is generated based on the link capacity of The traffic matrix is generated based on the link capacity of
topology. It can result in many kinds of situations, such as topology. It can result in many kinds of situations, such as
congestion, mild congestion and non-congestion. congestion, mild congestion and non-congestion.
In CCDR simulation, the traffic matrix is 500*500. About 20% links In CCDR simulation, the dimension of the traffic matrix is 500*500.
are overloaded when the Open Shortest Path First (OSPF) protocol is About 20% links are overloaded when the Open Shortest Path First
used in the network. (OSPF) protocol is used in the network.
4.3. CCDR End-to-End Path Optimization 4.3. CCDR End-to-End Path Optimization
The CCDR end-to-end path optimization is to find the best end-to-end The CCDR end-to-end path optimization is to find the best path which
path which is the lowest in metric value and each link of the path is is the lowest in metric value and each link of the path is far below
far below link's threshold. Based on the current state of the link's threshold. Based on the current state of the network, PCE
network, PCE within CCDR architecture combines the shortest path within CCDR framework combines the shortest path algorithm with
algorithm with penalty theory of classical optimization and graph penalty theory of classical optimization and graph theory.
theory.
Given background traffic matrix which is unscheduled, when a set of Given background traffic matrix which is unscheduled, when a set of
new flows comes into the network, the end-to-end path optimization new flows comes into the network, the end-to-end path optimization
finds the optimal paths for them. The selected paths bring the least finds the optimal paths for them. The selected paths bring the least
congestion degree to the network. congestion degree to the network.
The link utilization increment degree(UID) when the new flows are The link utilization increment degree(UID) when the new flows are
added into the network is shown in Fig.6. The first graph in Fig.6 added into the network is shown in Fig.6. The first graph in Fig.6
is the UID with OSPF and the second graph is the UID with CCDR end- is the UID with OSPF and the second graph is the UID with CCDR end-
to-end path optimization. The average UID of graph one is more than to-end path optimization. The average UID of graph one is more than
skipping to change at page 8, line 51 skipping to change at page 8, line 48
UID(%)| | UID(%)| |
| | | |
| | | |
20| | 20| |
| *| | *|
| * *| | * *|
| * * * * * ** * *| | * * * * * ** * *|
0+-----------------------------------------------------------+ 0+-----------------------------------------------------------+
0 100 200 300 400 500 600 700 800 900 1000 0 100 200 300 400 500 600 700 800 900 1000
Flow Number Flow Number
Fig.6 Simulation result with congestion elimination Fig.6 Simulation Result with Congestion Elimination
4.4. Network temporal congestion elimination 4.4. Network Temporal Congestion Elimination
Different degree of network congestion is simulated. The congestion Different degree of network congestions are simulated. The
degree (CD) is defined as the link utilization beyond its threshold. congestion degree (CD) is defined as the link utilization beyond its
threshold.
The CCDR congestion elimination performance is shown in Fig.7. The The CCDR congestion elimination performance is shown in Fig.7. The
first graph is the congestion degree before the process of congestion first graph is the congestion degree before the process of congestion
elimination. The average CD of all congested links is more than 10%. elimination. The average CD of all congested links is more than 10%.
The second graph shown in Fig.7 is the congestion degree after The second graph shown in Fig.7 is the congestion degree after
congestion elimination process. It shows only 12 links among totally congestion elimination process. It shows only 12 links among totally
20000 links exceed the threshold, and all the congestion degree is 20000 links exceed the threshold, and all the congestion degree is
less than 3%. Thus, after schedule of the traffic in congestion less than 3%. Thus, after scheduling of the traffic in congestion
paths, the degree of network congestion is greatly eliminated and the paths, the degree of network congestion is greatly eliminated and the
network utilization is in balance. network utilization is in balance.
Before congestion elimination Before congestion elimination
+-----------------------------------------------------------+ +-----------------------------------------------------------+
| * ** * ** ** *| | * ** * ** ** *|
20| * * **** * ** ** *| 20| * * **** * ** ** *|
|* * ** * ** ** **** * ***** *********| |* * ** * ** ** **** * ***** *********|
|* * * * * **** ****** * ** *** **********************| |* * * * * **** ****** * ** *** **********************|
15|* * * ** * ** **** ********* *****************************| 15|* * * ** * ** **** ********* *****************************|
skipping to change at page 10, line 41 skipping to change at page 10, line 41
CD(%) | | CD(%) | |
10| | 10| |
| | | |
| | | |
5 | | 5 | |
| | | |
| * ** * * * ** * ** * | | * ** * * * ** * ** * |
0 +-----------------------------------------------------------+ 0 +-----------------------------------------------------------+
0 0.5 1 1.5 2 0 0.5 1 1.5 2
Link Number(*10000) Link Number(*10000)
Fig.7 Simulation result with congestion elimination Fig.7 Simulation Result with Congestion Elimination
5. CCDR Deployment Consideration. 5. CCDR Deployment Consideration.
With the above CCDR scenarios and simulation results, we can know it With the above CCDR scenarios and simulation results, we can know it
is necessary and feasible to find one general solution to cope with is necessary and feasible to find one general solution to cope with
various complex situations for the most complex optimal path various complex situations for the complex optimal path computation
computation in centrally manner based on the underlay network in centrally manner based on the underlay network topology and the
topology and the real time traffic. real time traffic.
[I-D.ietf-teas-pce-native-ip] gives the principle solution for above [I-D.ietf-teas-pce-native-ip] gives the solution for above scenarios,
scenarios, such thoughts can be extended to cover requirements that such thoughts can be extended to cover requirements in other
are more concretes in future. situations in future.
6. Security Considerations 6. Security Considerations
This document considers mainly the integration of traditional This document considers mainly the integration of distributed
distributed protocol and the global view of central control. It protocol and the central control capability of PCE/SDN. It certainly
certainly can ease the management of network in various traffic- can ease the management of network in various traffic-engineering
engineering scenarios described in this document, but the central scenarios described in this document, but the central control manner
control manner may also bring the new point be easily attacked. also bring the new point that may be easily attacked. Solutions for
Solutions for CCDR scenarios should keep these in mind and consider CCDR scenarios should keep these in mind and consider more for the
more for the protection of SDN controller and their communication protection of PCE/SDN controller and their communication with the
with the underlay devices, which described in document 1 and underlay devices, as that described in document [RFC5440] and
[RFC8253] [RFC8253]
7. IANA Considerations 7. IANA Considerations
This document does not require any IANA actions. This document does not require any IANA actions.
8. Normative References 8. Contributors
Lu Huang contributes to the content of this draft.
9. Acknowledgement
The author would like to thank Deborah Brungard, Adrian Farrel,
Huaimo Chen, Vishnu Beeram and Lou Berger for their supports and
comments on this draft.
10. Normative References
[I-D.ietf-teas-pce-native-ip] [I-D.ietf-teas-pce-native-ip]
Wang, A., Zhao, Q., Khasanov, B., and K. Mi, "PCE in Wang, A., Zhao, Q., Khasanov, B., Chen, H., Mi, P.,
Native IP Network", draft-ietf-teas-pce-native-ip-00 (work Mallya, R., and S. Peng, "PCE in Native IP Network",
in progress), February 2018. draft-ietf-teas-pce-native-ip-01 (work in progress), June
2018.
[I-D.ietf-teas-pcecc-use-cases] [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Zhao, Q., Li, Z., Khasanov, B., Ke, Z., Fang, L., Zhou, Requirement Levels", BCP 14, RFC 2119,
C., Communications, T., and A. Rachitskiy, "The Use Cases DOI 10.17487/RFC2119, March 1997,
for Using PCE as the Central Controller(PCECC) of LSPs", <https://www.rfc-editor.org/info/rfc2119>.
draft-ietf-teas-pcecc-use-cases-01 (work in progress), May
2017.
[RFC5440] Vasseur, JP., Ed. and JL. Le Roux, Ed., "Path Computation [RFC5440] Vasseur, JP., Ed. and JL. Le Roux, Ed., "Path Computation
Element (PCE) Communication Protocol (PCEP)", RFC 5440, Element (PCE) Communication Protocol (PCEP)", RFC 5440,
DOI 10.17487/RFC5440, March 2009, DOI 10.17487/RFC5440, March 2009,
<https://www.rfc-editor.org/info/rfc5440>. <https://www.rfc-editor.org/info/rfc5440>.
[RFC8253] Lopez, D., Gonzalez de Dios, O., Wu, Q., and D. Dhody, [RFC8253] Lopez, D., Gonzalez de Dios, O., Wu, Q., and D. Dhody,
"PCEPS: Usage of TLS to Provide a Secure Transport for the "PCEPS: Usage of TLS to Provide a Secure Transport for the
Path Computation Element Communication Protocol (PCEP)", Path Computation Element Communication Protocol (PCEP)",
RFC 8253, DOI 10.17487/RFC8253, October 2017, RFC 8253, DOI 10.17487/RFC8253, October 2017,
<https://www.rfc-editor.org/info/rfc8253>. <https://www.rfc-editor.org/info/rfc8253>.
[RFC8283] Farrel, A., Ed., Zhao, Q., Ed., Li, Z., and C. Zhou, "An
Architecture for Use of PCE and the PCE Communication
Protocol (PCEP) in a Network with Central Control",
RFC 8283, DOI 10.17487/RFC8283, December 2017,
<https://www.rfc-editor.org/info/rfc8283>.
Authors' Addresses Authors' Addresses
Aijun Wang Aijun Wang
China Telecom China Telecom
Beiqijia Town, Changping District Beiqijia Town, Changping District
Beijing, Beijing 102209 Beijing, Beijing 102209
China China
Email: wangaj.bri@chinatelecom.cn Email: wangaj.bri@chinatelecom.cn
skipping to change at page 13, line 4 skipping to change at page 13, line 4
Email: koucx@lsec.cc.ac.cn Email: koucx@lsec.cc.ac.cn
Zhenqiang Li Zhenqiang Li
China Mobile China Mobile
32 Xuanwumen West Ave, Xicheng District 32 Xuanwumen West Ave, Xicheng District
Beijing 100053 Beijing 100053
China China
Email: li_zhenqiang@hotmail.com Email: li_zhenqiang@hotmail.com
Lu Huang
Huawei Technologies
Unit 7 NO 8.XiBinHe Road,YongDingMen
Beijing, Dongcheng District 100077
China
Email: hlisname@yahoo.com
Penghui Mi Penghui Mi
Huawei Technologies Huawei Technologies
Tower C of Bldg.2, Cloud Park, No.2013 of Xuegang Road Tower C of Bldg.2, Cloud Park, No.2013 of Xuegang Road
Shenzhen, Bantian,Longgang District 518129 Shenzhen, Bantian,Longgang District 518129
China China
Email: mipenghui@huawei.com Email: mipenghui@huawei.com
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