draft-ietf-teas-native-ip-scenarios-06.txt   draft-ietf-teas-native-ip-scenarios-07.txt 
TEAS Working Group A. Wang TEAS Working Group A. Wang
Internet-Draft China Telecom Internet-Draft China Telecom
Intended status: Informational X. Huang Intended status: Informational X. Huang
Expires: January 2, 2020 C. Kou Expires: February 27, 2020 C. Kou
BUPT BUPT
Z. Li Z. Li
China Mobile China Mobile
P. Mi P. Mi
Huawei Technologies Huawei Technologies
July 1, 2019 August 26, 2019
Scenarios and Simulation Results of PCE in Native IP Network Scenarios and Simulation Results of PCE in Native IP Network
draft-ietf-teas-native-ip-scenarios-06 draft-ietf-teas-native-ip-scenarios-07
Abstract Abstract
This document describes the scenarios and simulation results for PCE The requirements for the End to End(E2E) performance assurance are
in native IP network, which integrates the merit of distributed emerging within the service provider network, there are various
protocols (IGP/BGP), and the power of centrally control technologies solutions to meet such demands, but there is no one solution can meet
(PCE/SDN) to provide one feasible traffic engineering solution in these requirements in native IP network, especially one universal
various complex scenarios for the service provider. solution can cover intra-domain and inter-domain scenarios together.
This document describes the scenarios and simulation results for Path
Computation Elements (PCE) in native IP network, which integrates the
advantage of distributed protocols, and the power of centrally
control technologies to provide one feasible traffic engineering
solution in various complex scenarios for the service provider.
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.
Internet-Drafts are working documents of the Internet Engineering Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute Task Force (IETF). Note that other groups may also distribute
working documents as Internet-Drafts. The list of current Internet- working documents as Internet-Drafts. The list of current Internet-
Drafts is at https://datatracker.ietf.org/drafts/current/. Drafts is at https://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress." material or to cite them other than as "work in progress."
This Internet-Draft will expire on January 2, 2020. This Internet-Draft will expire on February 27, 2020.
Copyright Notice Copyright Notice
Copyright (c) 2019 IETF Trust and the persons identified as the Copyright (c) 2019 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
(https://trustee.ietf.org/license-info) in effect on the date of (https://trustee.ietf.org/license-info) in effect on the date of
publication of this document. Please review these documents publication of this document. Please review these documents
carefully, as they describe your rights and restrictions with respect carefully, as they describe your rights and restrictions with respect
to this document. Code Components extracted from this document must to this document. Code Components extracted from this document must
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. CCDR Scenarios. . . . . . . . . . . . . . . . . . . . . . . . 3 2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.1. QoS Assurance for Hybrid Cloud-based Application. . . . . 3 3. CCDR Scenarios. . . . . . . . . . . . . . . . . . . . . . . . 4
2.2. Link Utilization Maximization . . . . . . . . . . . . . . 4 3.1. QoS Assurance for Hybrid Cloud-based Application. . . . . 4
2.3. Traffic Engineering for Multi-Domain . . . . . . . . . . 5 3.2. Link Utilization Maximization . . . . . . . . . . . . . . 5
2.4. Network Temporal Congestion Elimination. . . . . . . . . 6 3.3. Traffic Engineering for Multi-Domain . . . . . . . . . . 6
3. CCDR Simulation. . . . . . . . . . . . . . . . . . . . . . . 6 3.4. Network Temporal Congestion Elimination. . . . . . . . . 7
3.1. Topology Simulation . . . . . . . . . . . . . . . . . . . 6 4. CCDR Simulation. . . . . . . . . . . . . . . . . . . . . . . 7
3.2. Traffic Matrix Simulation. . . . . . . . . . . . . . . . 7 4.1. Topology Simulation . . . . . . . . . . . . . . . . . . . 7
3.3. CCDR End-to-End Path Optimization . . . . . . . . . . . . 7 4.2. Traffic Matrix Simulation. . . . . . . . . . . . . . . . 8
3.4. Network Temporal Congestion Elimination . . . . . . . . . 9 4.3. CCDR End-to-End Path Optimization . . . . . . . . . . . . 8
4. CCDR Deployment Consideration. . . . . . . . . . . . . . . . 10 4.4. Network Temporal Congestion Elimination . . . . . . . . . 10
5. Security Considerations . . . . . . . . . . . . . . . . . . . 11 5. CCDR Deployment Consideration. . . . . . . . . . . . . . . . 11
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 11 6. Security Considerations . . . . . . . . . . . . . . . . . . . 12
7. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 11 7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 12
8. Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . 11 8. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 12
9. References . . . . . . . . . . . . . . . . . . . . . . . . . 11 9. Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . 12
9.1. Normative References . . . . . . . . . . . . . . . . . . 11 10. References . . . . . . . . . . . . . . . . . . . . . . . . . 12
9.2. Informative References . . . . . . . . . . . . . . . . . 12 10.1. Normative References . . . . . . . . . . . . . . . . . . 12
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 12 10.2. Informative References . . . . . . . . . . . . . . . . . 13
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 13
1. Introduction 1. Introduction
Service provider network is composed thousands of routers that run Service provider network is composed of thousands of routers that run
distributed protocol to exchange the reachability information between distributed protocol to exchange the reachability information between
them. The path for the destination network is mainly calculated and them. The path for the destination network is mainly calculated and
controlled by the IGP/BGP protocols. These distributed protocols are controlled by the distributed protocols. These distributed protocols
robust enough to support the current evolution of Internet but have are robust enough to support the current evolution of Internet but
some difficulties when application requires the end-to-end QoS have some difficulties when application requires the E2E performance
performance, or in the situation that the service provider wants to assurance, or in the situation that the service provider wants to
maximize the link utilization within their network. maximize the link utilization within their network.
MPLS-TE technology [RFC3209]is one solution for finely planned Multiprotocol Label Switching (MPLS) for Traffic Engineering(TE)
network but it will put heavy burden on the routers when we use it to technology [RFC3209]is one solution for finely planned network but it
meet the dynamic QoS assurance requirements within real time traffic mainly applies to the MPLS network. Even for MPLS network, the MPLS-
network. TE technology is often used for Label Switched Path (LSP) protection.
It is seldom used for dynamic performance assurance requirements
within real time traffic network.
SR(Segment Routing) [RFC8402] is another solution that integrates Segment Routing [RFC8402] is another solution that integrates some
some merits of distributed protocol and the advantages of centrally advantages of distributed protocol and centrally control mode, but it
control mode, but it requires the underlying network, especially the requires the underlying network, especially the provider edge router
provider edge router to do label push and pop action in-depth, and to do label push and pop action in-depth, and need complex mechanism
need complex mechanic for coexisting with the Non-SR network. for coexisting with the Non-Segment Routing network. Additionally,
Additionally, it can only maneuver the end-to-end path for MPLS and it can only maneuver the E2E path for MPLS and IPv6 traffic via
IPv6 traffic via different mechanisms. different mechanisms.
DetNet[RFC8578] describes use cases for diverse industries that have Deterministic Networking (DetNet)[RFC8578] describes use cases for
a common need for "deterministic flows", which can provide guaranteed diverse industries that have a common need for "deterministic flows",
bandwidth, bounded latency, and other properties germane to the which can provide guaranteed bandwidth, bounded latency, and other
transport of time-sensitive data. The use cases focus mainly on the properties germane to the transport of time-sensitive data. The use
industrial critical applications within one centrally controlled cases focus mainly on the industrial critical applications within one
network and are out of scope of this draft. centrally controlled network and are out of scope of this draft.
This draft describes scenarios that the centrally control dynamic This draft describes scenarios in native IP network that the
routing (CCDR) framework can easily solve, without the change of the Centrally Control Dynamic Routing (CCDR) framework can easily solve,
data plane behaviour on the router. It also gives the path without the change of the data plane behaviour on the router. It
optimization simulation results to illustrate the applicability of also gives the path optimization simulation results to illustrate the
CCDR framework. applicability of CCDR framework.
2. CCDR Scenarios. 2. Terminology
This document uses the following terms defined in [RFC5440]: PCE.
The following terms are defined in this document:
o BRAS: Broadband Remote Access Server
o CD: Congestion Degree
o CR: Core Router
o CCDR: Central Control Dynamic Routing
o E2E: End to End
o IDC: Internet Data Center
o MAN: Metro Area Network
o QoS: Quality of Service
o SR: Service Router
o UID: Utilization Increment Degree
o WAN: Wide Area Network
3. CCDR Scenarios.
The following sections describe some scenarios that the CCDR The following sections describe some scenarios that the CCDR
framework is suitable for deployment. framework is suitable for deployment.
2.1. 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 cloud putting more and more services on the public oriented cloud
environment, but keep core business within their private cloud. The environment, but keep core business within their private cloud. The
communication between the private and public cloud sites will span communication between the private and public cloud sites will span
the WAN network. The bandwidth requirements between them are the Wide Area Network (WAN) network. The bandwidth requirements
variable and the background traffic between these two sites changes between them are variable and the background traffic between these
from time to time. Enterprise applications just want to exploit the two sites changes from time to time. Enterprise applications just
network capabilities to assure the end-to-end QoS performance on want to exploit the network capabilities to assure the E2E Quality of
demand. Service(QoS) performance on demand.
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 framework is illustrated below: possible solution framework is illustrated below:
+------------------------+ +------------------------+
| Cloud Based Application| | Cloud Based Application|
+------------------------+ +------------------------+
| |
+-----------+ +-----------+
skipping to change at page 4, line 21 skipping to change at page 4, line 51
+-----------+ +-----------+
| |
| |
//--------------\\ //--------------\\
///// \\\\\ ///// \\\\\
Private Cloud Site || Distributed |Public Cloud Site Private Cloud Site || Distributed |Public Cloud Site
| Control Network | | Control Network |
\\\\\ ///// \\\\\ /////
\\--------------// \\--------------//
Fig.1 Hybrid Cloud Communication Scenario Figure 1: Hybrid Cloud Communication Scenario
By default, the traffic path between the private and public cloud By default, the traffic path between the private and public cloud
site will be determined by the distributed control network. When site will be determined by the distributed control network. When
applications require the end-to-end QoS assurance, it can send these applications require the E2E QoS assurance, it can send these
requirements to PCE,let PCE compute one e2e path which is based on requirements to PCE, let PCE compute one E2E path which is based on
the underlying network topology and the real traffic information, to the underlying network topology and the real traffic information, to
accommodate the application's QoS requirements. The proposed accommodate the application's QoS requirements. The proposed
solution can refer the draft [I-D.ietf-teas-pce-native-ip]. solution can refer the draft [I-D.ietf-teas-pce-native-ip].
Section 4 describes the detail simulation process and the result. Section 4 describes the detail simulation process and the result.
2.2. Link Utilization Maximization 3.2. Link Utilization Maximization
Network topology within MAN is generally in star mode as illustrated Network topology within Metro Area Network (MAN) is generally in star
in Fig.2, with different devices connect different customer types. mode as illustrated in Figure 2, with different devices connect
The traffic from these customers is often in tidal pattern that the different customer types. The traffic from these customers is often
links between the CR/BRAS and CR/SR will experience congestion in in tidal pattern that the links between the Core Router(CR)/Broadband
different periods, because the subscribers under BRAS often use the Remote Access Server(BRAS) and CR/Service Router(SR) will experience
network at night and the dedicated line users under SR often use the congestion in different periods, because the subscribers under BRAS
network during the daytime. The uplink between BRAS/SR and CR must often use the network at night and the dedicated line users under SR
satisfy the maximum traffic volume between them respectively and this often use the network during the daytime. The uplink between BRAS/SR
causes these links often in underutilization situation. and CR must satisfy the maximum traffic volume between them
respectively and this causes these links often in underutilization
situation.
+--------+ +--------+
| CR | | CR |
+----|---+ +----|---+
| |
--------|--------|-------| --------|--------|-------|
| | | | | | | |
+--|-+ +-|- +--|-+ +-|+ +--|-+ +-|- +--|-+ +-|+
|BRAS| |SR| |BRAS| |SR| |BRAS| |SR| |BRAS| |SR|
+----+ +--+ +----+ +--+ +----+ +--+ +----+ +--+
Fig.2 Star-mode Network Topology within MAN Figure 2: Star-mode Network Topology within MAN
If we consider to connect the BRAS/SR with local link loop (which is If we consider to connect the BRAS/SR with local link loop (which is
more cheaper), and control the MAN with the CCDR framework, we can more cheaper), and control the MAN with the CCDR framework, we can
exploit the tidal phenomena between BRAS/CR and SR/CR links, maximize exploit the tidal phenomena between BRAS/CR and SR/CR links, maximize
the links (which is more expensive) utilization of them . the links (which is more expensive) utilization of them .
+-------+ +-------+
----- PCE | ----- PCE |
| +-------+ | +-------+
+----|---+ +----|---+
| CR | | CR |
+----|---+ +----|---+
| |
--------|--------|-------| --------|--------|-------|
| | | | | | | |
+--|-+ +-|- +--|-+ +-|+ +--|-+ +-|- +--|-+ +-|+
|BRAS-----SR| |BRAS-----SR| |BRAS-----SR| |BRAS-----SR|
+----+ +--+ +----+ +--+ +----+ +--+ +----+ +--+
Fig.3 Link Utilization Maximization via CCDR Figure 3: Link Utilization Maximization via CCDR
2.3. Traffic Engineering for Multi-Domain 3.3. Traffic Engineering for Multi-Domain
Operator's networks are often comprised by different domains, The service provider networks are often comprised of different
interconnected with each other,form very complex topology that domains, interconnected with each other,form very complex topology
illustrated in Fig.4. Due to the traffic pattern to/from MAN and that illustrated in Figure.4. Due to the traffic pattern to/from MAN
IDC, the utilization of links between them are often asymmetric. It and IDC, the utilization of links between them are often asymmetric.
is almost impossible to balance the utilization of these links via It is almost impossible to balance the utilization of these links via
the distributed protocol, but this unbalance phenomenon can be the distributed protocol, but this unbalance phenomenon can be
overcome via the CCDR framework. overcome via the CCDR framework.
+---+ +---+ +---+ +---+
|MAN|-----------------IDC| |MAN|-----------------IDC|
+-|-| | +-|-+ +-|-| | +-|-+
| ---------| | | ---------| |
------|BackBone|------ ------|BackBone|------
| ----|----| | | ----|----| |
| | | | | |
+-|-- | ----+ +-|-- | ----+
|IDC|----------------|MAN| |IDC|----------------|MAN|
+---| |---+ +---| |---+
Fig.4 Traffic Engineering for Complex Multi-Domain Topology Figure 4: Traffic Engineering for Complex Multi-Domain Topology
Solution for this scenario requires the gather of NetFlow Solution for this scenario requires the gather of NetFlow
information, analysis the source/destination AS of them and determine information, analysis the source/destination AS of them and determine
which pair is the main cause of the congested link. After this, the what is the main cause of the congested link. After this, the
operator can use the multi eBGP sessions described in operator can use the multi external Border Gateway Protocol(eBGP)
[I-D.ietf-teas-pce-native-ip]to schedule the traffic among different sessions described in [I-D.ietf-teas-pce-native-ip]to schedule the
domains. traffic among different domains.
2.4. Network Temporal Congestion Elimination. 3.4. Network Temporal Congestion Elimination.
In more general situation, there are often temporal congestions In more general situation, there are often temporal congestions
within the service provider's network. Such congestion phenomena within the service provider's network. Such congestion phenomena
often appear repeatedly and if the service provider has some methods often appear repeatedly and if the service provider has some methods
to mitigate it, it will certainly increase the degree of satisfaction to mitigate it, it will certainly increase the degree of satisfaction
for their customers. CCDR is also suitable for such scenario in such for their customers. CCDR is also suitable for such scenario in such
manner that the distributed protocol process most of the traffic manner that the distributed protocol process most of the traffic
forwarding and the controller schedule some traffic out of the forwarding and the controller schedule some traffic out of the
congestion links to lower the utilization of them. Section 4 congestion links to lower the utilization of them. Section 4
describes the simulation process and results about such scenario. describes the simulation process and results about such scenario.
3. CCDR Simulation. 4. CCDR Simulation.
The following sections describe the topology, traffic matrix, end-to- The following sections describe the topology, traffic matrix, E2E
end path optimization and congestion elimination in CCDR applied path optimization and congestion elimination in CCDR applied
scenarios. scenarios.
3.1. 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 node and edge node. 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. Figure 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|\
| +----+ | | +----+ |
| | | |
| | | |
+----+ +----+ +----+ +----+ +----+ +----+
|Edge|----|Core|-----|Core|---------+ |Edge|----|Core|-----|Core|---------+
skipping to change at page 7, line 26 skipping to change at page 8, line 26
+----+ | / \ | | +----+ | / \ | |
\ | / \ | | \ | / \ | |
+----+ +----+ +----+ | +----+ +----+ +----+ |
|Edge|----|Core|-----|Core| | |Edge|----|Core|-----|Core| |
+----+ +----+ +----+ | +----+ +----+ +----+ |
| | | | | |
| +------\ +----+ | +------\ +----+
| ---|Edge| | ---|Edge|
+-----------------/ +----+ +-----------------/ +----+
Fig.5 Topology of Simulation Figure 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.
3.2. 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 dimension of the traffic matrix is 500*500. In CCDR simulation, the dimension of the traffic matrix is 500*500.
About 20% links are overloaded when the Open Shortest Path First About 20% links are overloaded when the Open Shortest Path First
(OSPF) protocol is used in the network. (OSPF) protocol is used in the network.
3.3. 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 path which The CCDR E2E path optimization is to find the best path which is the
is the lowest in metric value and each link of the path is far below lowest in metric value and each link of the path is far below link's
link's threshold. Based on the current state of the network, PCE threshold. Based on the current state of the network, PCE within
within CCDR framework combines the shortest path algorithm with CCDR framework combines the shortest path algorithm with penalty
penalty theory of classical optimization and graph theory. theory of classical optimization and graph 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 E2E path optimization finds the
finds the optimal paths for them. The selected paths bring the least 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 Figure 6. The first graph in
is the UID with OSPF and the second graph is the UID with CCDR end- Figure 6 is the UID with OSPF and the second graph is the UID with
to-end path optimization. The average UID of the first graph is more CCDR E2E path optimization. The average UID of the first graph is
than 30%. After path optimization, the average UID is less than 5%. more than 30%. After path optimization, the average UID is less than
The results show that the CCDR end-to-end path optimization has an 5%. The results show that the CCDR E2E path optimization has an eye-
eye-catching decreasing in UID relative to the path chosen based on catching decreasing in UID relative to the path chosen based on OSPF.
OSPF.
+-----------------------------------------------------------+ +-----------------------------------------------------------+
| * * * *| | * * * *|
60| * * * * * *| 60| * * * * * *|
|* * ** * * * * * ** * * * * **| |* * ** * * * * * ** * * * * **|
|* * ** * * ** *** ** * * ** * * * ** * * *** **| |* * ** * * ** *** ** * * ** * * * ** * * *** **|
|* * * ** * ** ** *** *** ** **** ** *** **** ** *** **| |* * * ** * ** ** *** *** ** **** ** *** **** ** *** **|
40|* * * ***** ** *** *** *** ** **** ** *** ***** ****** **| 40|* * * ***** ** *** *** *** ** **** ** *** ***** ****** **|
UID(%)|* * ******* ** *** *** ******* **** ** *** ***** *********| UID(%)|* * ******* ** *** *** ******* **** ** *** ***** *********|
|*** ******* ** **** *********** *********** ***************| |*** ******* ** **** *********** *********** ***************|
skipping to change at page 8, line 49 skipping to change at page 9, 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 Figure 6: Simulation Result with Congestion Elimination
3.4. Network Temporal Congestion Elimination 4.4. Network Temporal Congestion Elimination
Different degree of network congestions are simulated. The Different degree of network congestions are simulated. The
congestion degree (CD) is defined as the link utilization beyond its Congestion Degree (CD) is defined as the link utilization beyond its
threshold. threshold.
The CCDR congestion elimination performance is shown in Fig.7. The The CCDR congestion elimination performance is shown in Figure 7.
first graph is the congestion degree before the process of congestion The first graph is the CD distribution before the process of
elimination. The average CD of all congested links is more than 10%. congestion elimination. The average CD of all congested links is
The second graph shown in Fig.7 is the congestion degree after more than 10%. The second graph shown in Figure 7 is the CD
congestion elimination process. It shows only 12 links among totally distribution after congestion elimination process. It shows only 12
20000 links exceed the threshold, and all the congestion degree is links among totally 20000 links exceed the threshold, and all the CD
less than 3%. Thus, after scheduling of the traffic in congestion values are less than 3%. Thus, after scheduling of the traffic in
paths, the degree of network congestion is greatly eliminated and the congestion paths, the degree of network congestion is greatly
network utilization is in balance. eliminated and the network utilization is in balance.
Before congestion elimination Before congestion elimination
+-----------------------------------------------------------+ +-----------------------------------------------------------+
| * ** * ** ** *| | * ** * ** ** *|
20| * * **** * ** ** *| 20| * * **** * ** ** *|
|* * ** * ** ** **** * ***** *********| |* * ** * ** ** **** * ***** *********|
|* * * * * **** ****** * ** *** **********************| |* * * * * **** ****** * ** *** **********************|
15|* * * ** * ** **** ********* *****************************| 15|* * * ** * ** **** ********* *****************************|
|* * ****** ******* ********* *****************************| |* * ****** ******* ********* *****************************|
CD(%) |* ********* ******* ***************************************| CD(%) |* ********* ******* ***************************************|
skipping to change at page 10, line 41 skipping to change at page 11, 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 Figure 7: Simulation Result with Congestion Elimination
4. 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 complex optimal path computation various complex situations for the complex optimal path computation
in centrally manner based on the underlay network topology and the in centrally manner in native IP network based on the underlay
real time traffic. network topology and the real time traffic.
[I-D.ietf-teas-pce-native-ip] gives the solution for above scenarios, [I-D.ietf-teas-pce-native-ip] gives the solution for above scenarios,
such thoughts can be extended to cover requirements in other such thoughts can be extended to cover requirements in other
situations in future. situations in future.
5. Security Considerations 6. Security Considerations
This document considers mainly the integration of distributed This document considers mainly the integration of distributed
protocol and the central control capability of PCE/SDN. It certainly protocol and the central control capability of PCE. It certainly can
can ease the management of network in various traffic-engineering ease the management of network in various traffic engineering
scenarios described in this document, but the central control manner scenarios described in this document, but the central control manner
also bring the new point that may be easily attacked. Solutions for also bring the new point that may be easily attacked. Solutions for
CCDR scenarios should keep these in mind and consider more for the CCDR scenarios should keep these in mind and consider more for the
protection of PCE/SDN controller and their communication with the protection of PCEand their communication with the underlay devices,
underlay devices, as that described in document [RFC5440] and as that described in document [RFC5440] and [RFC8253]
[RFC8253]
6. IANA Considerations 7. IANA Considerations
This document does not require any IANA actions. This document does not require any IANA actions.
7. Contributors 8. Contributors
Lu Huang contributes to the content of this draft. Lu Huang contributes to the content of this draft.
8. Acknowledgement 9. Acknowledgement
The author would like to thank Deborah Brungard, Adrian Farrel, The author would like to thank Deborah Brungard, Adrian Farrel,
Huaimo Chen, Vishnu Beeram and Lou Berger for their supports and Huaimo Chen, Vishnu Beeram and Lou Berger for their supports and
comments on this draft. comments on this draft.
9. References 10. References
9.1. Normative References 10.1. Normative References
[I-D.ietf-teas-pce-native-ip] [I-D.ietf-teas-pce-native-ip]
Wang, A., Zhao, Q., Khasanov, B., Chen, H., and R. Mallya, Wang, A., Zhao, Q., Khasanov, B., Chen, H., and R. Mallya,
"PCE in Native IP Network", draft-ietf-teas-pce-native- "PCE in Native IP Network", draft-ietf-teas-pce-native-
ip-03 (work in progress), April 2019. ip-03 (work in progress), April 2019.
[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>.
9.2. Informative References 10.2. Informative References
[RFC3209] Awduche, D., Berger, L., Gan, D., Li, T., Srinivasan, V., [RFC3209] Awduche, D., Berger, L., Gan, D., Li, T., Srinivasan, V.,
and G. Swallow, "RSVP-TE: Extensions to RSVP for LSP and G. Swallow, "RSVP-TE: Extensions to RSVP for LSP
Tunnels", RFC 3209, DOI 10.17487/RFC3209, December 2001, Tunnels", RFC 3209, DOI 10.17487/RFC3209, December 2001,
<https://www.rfc-editor.org/info/rfc3209>. <https://www.rfc-editor.org/info/rfc3209>.
[RFC8402] Filsfils, C., Ed., Previdi, S., Ed., Ginsberg, L., [RFC8402] Filsfils, C., Ed., Previdi, S., Ed., Ginsberg, L.,
Decraene, B., Litkowski, S., and R. Shakir, "Segment Decraene, B., Litkowski, S., and R. Shakir, "Segment
Routing Architecture", RFC 8402, DOI 10.17487/RFC8402, Routing Architecture", RFC 8402, DOI 10.17487/RFC8402,
July 2018, <https://www.rfc-editor.org/info/rfc8402>. July 2018, <https://www.rfc-editor.org/info/rfc8402>.
skipping to change at page 12, line 35 skipping to change at page 13, line 29
<https://www.rfc-editor.org/info/rfc8578>. <https://www.rfc-editor.org/info/rfc8578>.
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: wangaj3@chinatelecom.cn
Xiaohong Huang Xiaohong Huang
Beijing University of Posts and Telecommunications Beijing University of Posts and Telecommunications
No.10 Xitucheng Road, Haidian District No.10 Xitucheng Road, Haidian District
Beijing Beijing
China China
Email: huangxh@bupt.edu.cn Email: huangxh@bupt.edu.cn
Caixia Kou Caixia Kou
Beijing University of Posts and Telecommunications Beijing University of Posts and Telecommunications
No.10 Xitucheng Road, Haidian District No.10 Xitucheng Road, Haidian District
Beijing Beijing
China China
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
Penghui Mi Penghui Mi
Huawei Technologies Huawei Technologies
 End of changes. 55 change blocks. 
142 lines changed or deleted 178 lines changed or added

This html diff was produced by rfcdiff 1.47. The latest version is available from http://tools.ietf.org/tools/rfcdiff/