draft-ietf-teas-native-ip-scenarios-07.txt   draft-ietf-teas-native-ip-scenarios-08.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: February 27, 2020 C. Kou Expires: March 2, 2020 C. Kou
BUPT BUPT
Z. Li Z. Li
China Mobile China Mobile
P. Mi P. Mi
Huawei Technologies Huawei Technologies
August 26, 2019 August 30, 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-07 draft-ietf-teas-native-ip-scenarios-08
Abstract Abstract
The requirements for the End to End(E2E) performance assurance are Requirements for providing the End to End(E2E) performance assurance
emerging within the service provider network, there are various are emerging within the service provider network. While there are
solutions to meet such demands, but there is no one solution can meet various technology solutions, there is no one solution which can
these requirements in native IP network, especially one universal fulfill these requirements for a native IP network. One universal
solution can cover intra-domain and inter-domain scenarios together. (E2E) solution which can cover both intra-domain and inter-domain
scenarios is needed.
This document describes the scenarios and simulation results for Path One feasible E2E traffic engineering solution is the use of a Path
Computation Elements (PCE) in native IP network, which integrates the Computation Elements (PCE) in a native IP network. This document
advantage of distributed protocols, and the power of centrally describes various complex scenarios and simulation results when
control technologies to provide one feasible traffic engineering applying a PCE in a native IP network. This solution, referred to as
solution in various complex scenarios for the service provider. Centralized Control Dynamic Routing (CCDR), integrates the advantage
of using distributed protocols and the power of a centralized control
technology.
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 February 27, 2020. This Internet-Draft will expire on March 2, 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
skipping to change at page 2, line 41 skipping to change at page 2, line 41
4.2. Traffic Matrix Simulation. . . . . . . . . . . . . . . . 8 4.2. Traffic Matrix Simulation. . . . . . . . . . . . . . . . 8
4.3. CCDR End-to-End Path Optimization . . . . . . . . . . . . 8 4.3. CCDR End-to-End Path Optimization . . . . . . . . . . . . 8
4.4. Network Temporal Congestion Elimination . . . . . . . . . 10 4.4. Network Temporal Congestion Elimination . . . . . . . . . 10
5. CCDR Deployment Consideration. . . . . . . . . . . . . . . . 11 5. CCDR Deployment Consideration. . . . . . . . . . . . . . . . 11
6. Security Considerations . . . . . . . . . . . . . . . . . . . 12 6. Security Considerations . . . . . . . . . . . . . . . . . . . 12
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 12 7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 12
8. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 12 8. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 12
9. Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . 12 9. Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . 12
10. References . . . . . . . . . . . . . . . . . . . . . . . . . 12 10. References . . . . . . . . . . . . . . . . . . . . . . . . . 12
10.1. Normative References . . . . . . . . . . . . . . . . . . 12 10.1. Normative References . . . . . . . . . . . . . . . . . . 12
10.2. Informative References . . . . . . . . . . . . . . . . . 13 10.2. Informative References . . . . . . . . . . . . . . . . . 12
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 13 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 13
1. Introduction 1. Introduction
Service provider network is composed of thousands of routers that run A service provider network is composed of thousands of routers that
distributed protocol to exchange the reachability information between run distributed protocols to exchange the reachability information.
them. The path for the destination network is mainly calculated and The path for the destination network is mainly calculated, and
controlled by the distributed protocols. These distributed protocols controlled, by the distributed protocols. These distributed
are robust enough to support the current evolution of Internet but protocols are robust enough to support most applications, but have
have some difficulties when application requires the E2E performance some difficulties supporting the complexities needed for traffic
assurance, or in the situation that the service provider wants to engineering applications, e.g. E2E performance assurance, or
maximize the link utilization within their network. maximizing the link utilization within an IP network.
Multiprotocol Label Switching (MPLS) for Traffic Engineering(TE) Multiprotocol Label Switching (MPLS) using Traffic Engineering (TE)
technology [RFC3209]is one solution for finely planned network but it technology (MPLS-TE)[RFC3209]is one solution for traffic engineering
mainly applies to the MPLS network. Even for MPLS network, the MPLS- network but it introduces an MPLS network and related technology
TE technology is often used for Label Switched Path (LSP) protection. which would be an overlay of the IP network. MPLS-TE technology is
It is seldom used for dynamic performance assurance requirements often used for Label Switched Path (LSP) protection and complex path
within real time traffic network. set-up within a domain.
It has not been widely deployed for meeting E2E (especially in inter-
domain) dynamic performance assurance requirements for an IP network.
Segment Routing [RFC8402] is another solution that integrates some Segment Routing [RFC8402] is another solution that integrates some
advantages of distributed protocol and centrally control mode, but it advantages of using a distributed protocol and a centrally control
requires the underlying network, especially the provider edge router technology, but it requires the underlying network, especially the
to do label push and pop action in-depth, and need complex mechanism provider edge router, to do a label push and pop action in-depth, and
for coexisting with the Non-Segment Routing network. Additionally, adds complexity, when coexisting with the Non-Segment Routing
it can only maneuver the E2E path for MPLS and IPv6 traffic via network. Additionally, it can only maneuver the E2E paths for MPLS
different mechanisms. and IPv6 traffic via different mechanisms.
Deterministic Networking (DetNet)[RFC8578] describes use cases for Deterministic Networking (DetNet)[RFC8578] is another possible
diverse industries that have a common need for "deterministic flows", solution. It is primarily focused on providing bounded latency for a
which can provide guaranteed bandwidth, bounded latency, and other flow and introduces additional requirements on the domain edge
properties germane to the transport of time-sensitive data. The use router. The current DetNet scope is within one domain. The use
cases focus mainly on the industrial critical applications within one cases defined in this document do not require the additional
centrally controlled network and are out of scope of this draft. complexity of deterministic properties and so differ from the DetNet
use cases.
This draft describes scenarios in native IP network that the This draft describes scenarios for a native IP network that a
Centrally Control Dynamic Routing (CCDR) framework can easily solve, Centralized Control Dynamic Routing (CCDR) framework can easily
without the change of the data plane behaviour on the router. It solve, without requiring a change of the data plane behaviour on the
also gives the path optimization simulation results to illustrate the router. It also provides path optimization simulation results to
applicability of CCDR framework. illustrate the applicability of the CCDR framework.
2. Terminology 2. Terminology
This document uses the following terms defined in [RFC5440]: PCE. This document uses the following terms defined in [RFC5440]: PCE.
The following terms are defined in this document: The following terms are defined in this document:
o BRAS: Broadband Remote Access Server o BRAS: Broadband Remote Access Server
o CD: Congestion Degree o CD: Congestion Degree
o CR: Core Router o CR: Core Router
o CCDR: Central Control Dynamic Routing o CCDR: Centralized Control Dynamic Routing
o E2E: End to End o E2E: End to End
o IDC: Internet Data Center o IDC: Internet Data Center
o MAN: Metro Area Network o MAN: Metro Area Network
o QoS: Quality of Service o QoS: Quality of Service
o SR: Service Router o SR: Service Router
o UID: Utilization Increment Degree o UID: Utilization Increment Degree
o WAN: Wide Area Network o WAN: Wide Area Network
skipping to change at page 4, line 16 skipping to change at page 4, line 20
o QoS: Quality of Service o QoS: Quality of Service
o SR: Service Router o SR: Service Router
o UID: Utilization Increment Degree o UID: Utilization Increment Degree
o WAN: Wide Area Network o WAN: Wide Area Network
3. CCDR Scenarios. 3. CCDR Scenarios.
The following sections describe some scenarios that the CCDR The following sections describe various deployment scenarios for
framework is suitable for deployment. applying the CCDR framework.
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 emergence of cloud computing technologies, enterprises are
putting more and more services on the public oriented cloud putting more and more services on a public oriented cloud
environment, but keep core business within their private cloud. The environment, but keeping core business within their private cloud.
communication between the private and public cloud sites will span The communication between the private and public cloud sites will
the Wide Area Network (WAN) network. The bandwidth requirements span the Wide Area Network (WAN) network. The bandwidth requirements
between them are variable and the background traffic between these between them are variable and the background traffic between these
two sites changes from time to time. Enterprise applications just two sites varies over time. Enterprise applications require
want to exploit the network capabilities to assure the E2E Quality of assurance of the E2E Quality of Service(QoS) performance on demand
Service(QoS) performance on demand. for variable bandwidth services.
CCDR, which integrates the merits of distributed protocol and the CCDR, which integrates the merits of distributed protocols and the
power of centrally control, is suitable for this scenario. The power of centralized 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|
+------------------------+ +------------------------+
| |
+-----------+ +-----------+
| PCE | | PCE |
+-----------+ +-----------+
| |
skipping to change at page 5, line 8 skipping to change at page 5, line 26
Private Cloud Site || Distributed |Public Cloud Site Private Cloud Site || Distributed |Public Cloud Site
| Control Network | | Control Network |
\\\\\ ///// \\\\\ /////
\\--------------// \\--------------//
Figure 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 E2E 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 the PCE, and let the PCE compute one E2E path which
the underlying network topology and the real traffic information, to is based on the underlying network topology and the real traffic
accommodate the application's QoS requirements. The proposed information, to accommodate the application's QoS requirements.
solution can refer the draft [I-D.ietf-teas-pce-native-ip]. Section 4 of this document describes the simulation results for this
Section 4 describes the detail simulation process and the result. use case.
3.2. Link Utilization Maximization 3.2. Link Utilization Maximization
Network topology within Metro Area Network (MAN) is generally in star Network topology within a Metro Area Network (MAN) is generally in a
mode as illustrated in Figure 2, with different devices connect star mode as illustrated in Figure 2, with different devices
different customer types. The traffic from these customers is often connected to different customer types. The traffic from these
in tidal pattern that the links between the Core Router(CR)/Broadband customers is often in a tidal pattern, with the links between the
Remote Access Server(BRAS) and CR/Service Router(SR) will experience Core Router(CR)/Broadband Remote Access Server(BRAS) and CR/Service
congestion in different periods, because the subscribers under BRAS Router(SR), experiencing congestion in different periods, because the
often use the network at night and the dedicated line users under SR subscribers under BRAS, often use the network at night, and the
often use the network during the daytime. The uplink between BRAS/SR dedicated line users under SR, often use the network during the
and CR must satisfy the maximum traffic volume between them daytime. The uplink between BRAS/SR and CR must satisfy the maximum
respectively and this causes these links often in underutilization traffic volume between them respectively and this causes these links
situation. often to be under-utilized.
+--------+ +--------+
| CR | | CR |
+----|---+ +----|---+
| |
--------|--------|-------| --------|--------|-------|
| | | | | | | |
+--|-+ +-|- +--|-+ +-|+ +--|-+ +-|- +--|-+ +-|+
|BRAS| |SR| |BRAS| |SR| |BRAS| |SR| |BRAS| |SR|
+----+ +--+ +----+ +--+ +----+ +--+ +----+ +--+
Figure 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 connecting the BRAS/SR with a local link loop (which
more cheaper), and control the MAN with the CCDR framework, we can is usually lower cost), and control the overall MAN topology with the
exploit the tidal phenomena between BRAS/CR and SR/CR links, maximize CCDR framework, we can exploit the tidal phenomena between the BRAS/
the links (which is more expensive) utilization of them . CR and SR/CR links, maximizing the utilization of these links (which
are usually higher cost).
+-------+ +-------+
----- PCE | ----- PCE |
| +-------+ | +-------+
+----|---+ +----|---+
| CR | | CR |
+----|---+ +----|---+
| |
--------|--------|-------| --------|--------|-------|
| | | | | | | |
+--|-+ +-|- +--|-+ +-|+ +--|-+ +-|- +--|-+ +-|+
|BRAS-----SR| |BRAS-----SR| |BRAS-----SR| |BRAS-----SR|
+----+ +--+ +----+ +--+ +----+ +--+ +----+ +--+
Figure 3: Link Utilization Maximization via CCDR Figure 3: Link Utilization Maximization via CCDR
3.3. Traffic Engineering for Multi-Domain 3.3. Traffic Engineering for Multi-Domain
The service provider networks are often comprised of different Service provider networks are often comprised of different domains,
domains, interconnected with each other,form very complex topology interconnected with each other,forming a very complex topology as
that illustrated in Figure.4. Due to the traffic pattern to/from MAN illustrated in Figure 4. Due to the traffic pattern to/from the MAN
and IDC, the utilization of links between them are often asymmetric. and IDC, the utilization of the links between them are often
It is almost impossible to balance the utilization of these links via asymmetric. It is almost impossible to balance the utilization of
the distributed protocol, but this unbalance phenomenon can be these links via a distributed protocol, but this unbalance can be
overcome via the CCDR framework. overcome utilizing the CCDR framework.
+---+ +---+ +---+ +---+
|MAN|-----------------IDC| |MAN|-----------------IDC|
+-|-| | +-|-+ +-|-| | +-|-+
| ---------| | | ---------| |
------|BackBone|------ ------|BackBone|------
| ----|----| | | ----|----| |
| | | | | |
+-|-- | ----+ +-|-- | ----+
|IDC|----------------|MAN| |IDC|----------------|MAN|
+---| |---+ +---| |---+
Figure 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 A solution for this scenario requires the gathering of NetFlow
information, analysis the source/destination AS of them and determine information, analysis of the source/destination AS, and determining
what 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 external Border Gateway Protocol(eBGP) operator can use the external Border Gateway Protocol(eBGP) sessions
sessions described in [I-D.ietf-teas-pce-native-ip]to schedule the to schedule the traffic among the different domains.
traffic among different domains.
3.4. Network Temporal Congestion Elimination. 3.4. Network Temporal Congestion Elimination.
In more general situation, there are often temporal congestions In more general situations, 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 methods to
to mitigate it, it will certainly increase the degree of satisfaction mitigate it, it will certainly improve their network operations
for their customers. CCDR is also suitable for such scenario in such capabilities and increase satisfaction for their customers. CCDR is
manner that the distributed protocol process most of the traffic also suitable for such scenarios, as the controller can schedule
forwarding and the controller schedule some traffic out of the traffic out of the congested links, lowering the utilization of them
congestion links to lower the utilization of them. Section 4 during these times. Section 4 describes the simulation results of
describes the simulation process and results about such scenario. this scenario.
4. CCDR Simulation. 4. CCDR Simulation.
The following sections describe the topology, traffic matrix, E2E The following sections describe the topology, traffic matrix, E2E
path optimization and congestion elimination in CCDR applied path optimization and congestion elimination in CCDR applied
scenarios. 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 node and edge node. Nodes used in the 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. Figure 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 this CCDR simulation,
core nodes and 400 edge nodes are generated. 100 core nodes and 400 edge nodes are generated.
+----+ +----+
/|Edge|\ /|Edge|\
| +----+ | | +----+ |
| | | |
| | | |
+----+ +----+ +----+ +----+ +----+ +----+
|Edge|----|Core|-----|Core|---------+ |Edge|----|Core|-----|Core|---------+
+----+ +----+ +----+ | +----+ +----+ +----+ |
/ | \ / | | / | \ / | |
skipping to change at page 8, line 30 skipping to change at page 8, line 30
+----+ +----+ +----+ | +----+ +----+ +----+ |
| | | | | |
| +------\ +----+ | +------\ +----+
| ---|Edge| | ---|Edge|
+-----------------/ +----+ +-----------------/ +----+
Figure 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 a 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 dimension of the traffic matrix is 500*500. In the CCDR simulation, the dimension of the traffic matrix is
About 20% links are overloaded when the Open Shortest Path First 500*500. About 20% links are overloaded when the Open Shortest Path
(OSPF) protocol is used in the network. First (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 E2E path optimization is to find the best path which is the The CCDR E2E path optimization is to find the best path which is the
lowest in metric value and each link of the path is far below link's lowest in metric value and each link of the path is far below link's
threshold. Based on the current state of the network, PCE within threshold. Based on the current state of the network, the PCE within
CCDR framework combines the shortest path algorithm with penalty CCDR framework combines the shortest path algorithm with a 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 a background traffic matrix, which is unscheduled, when a set
new flows comes into the network, the E2E path optimization finds the of new flows comes into the network, the E2E path optimization finds
optimal paths for them. The selected paths bring the least 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 Figure 6. The first graph in added into the network, is shown in Figure 6. The first graph in
Figure 6 is the UID with OSPF and the second graph is the UID with Figure 6 is the UID with OSPF and the second graph is the UID with
CCDR E2E path optimization. The average UID of the first graph is CCDR E2E path optimization. The average UID of the first graph is
more than 30%. After path optimization, the average UID is less than more than 30%. After path optimization, the average UID is less than
5%. The results show that the CCDR E2E path optimization has an eye- 5%. The results show that the CCDR E2E path optimization has an eye-
catching decreasing in UID relative to the path chosen based on OSPF. catching decrease in UID relative to the path chosen based on OSPF.
+-----------------------------------------------------------+ +-----------------------------------------------------------+
| * * * *| | * * * *|
60| * * * * * *| 60| * * * * * *|
|* * ** * * * * * ** * * * * **| |* * ** * * * * * ** * * * * **|
|* * ** * * ** *** ** * * ** * * * ** * * *** **| |* * ** * * ** *** ** * * ** * * * ** * * *** **|
|* * * ** * ** ** *** *** ** **** ** *** **** ** *** **| |* * * ** * ** ** *** *** ** **** ** *** **** ** *** **|
40|* * * ***** ** *** *** *** ** **** ** *** ***** ****** **| 40|* * * ***** ** *** *** *** ** **** ** *** ***** ****** **|
UID(%)|* * ******* ** *** *** ******* **** ** *** ***** *********| UID(%)|* * ******* ** *** *** ******* **** ** *** ***** *********|
|*** ******* ** **** *********** *********** ***************| |*** ******* ** **** *********** *********** ***************|
skipping to change at page 10, line 7 skipping to change at page 10, line 7
| *| | *|
| * *| | * *|
| * * * * * ** * *| | * * * * * ** * *|
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
Figure 6: Simulation Result with Congestion Elimination Figure 6: Simulation Result with Congestion Elimination
4.4. Network Temporal Congestion Elimination 4.4. Network Temporal Congestion Elimination
Different degree of network congestions are simulated. The Different degrees of network congestions were 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 Figure 7. The CCDR congestion elimination performance is shown in Figure 7.
The first graph is the CD distribution before the process of The first graph is the CD distribution before the process of
congestion elimination. The average CD of all congested links is congestion elimination. The average CD of all congested links is
more than 10%. The second graph shown in Figure 7 is the CD more than 10%. The second graph shown in Figure 7 is the CD
distribution after congestion elimination process. It shows only 12 distribution after using the congestion elimination process. It
links among totally 20000 links exceed the threshold, and all the CD shows only 12 links among totally 20000 links exceed the threshold,
values are less than 3%. Thus, after scheduling of the traffic in and all the CD values are less than 3%. Thus, after scheduling of the
congestion paths, the degree of network congestion is greatly traffic away from the congested paths, the degree of network
eliminated and the network utilization is in balance. congestion is greatly 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 11, line 45 skipping to change at page 11, line 45
5 | | 5 | |
| | | |
| * ** * * * ** * ** * | | * ** * * * ** * ** * |
0 +-----------------------------------------------------------+ 0 +-----------------------------------------------------------+
0 0.5 1 1.5 2 0 0.5 1 1.5 2
Link Number(*10000) Link Number(*10000)
Figure 7: Simulation Result with Congestion Elimination Figure 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 demonstrate
is necessary and feasible to find one general solution to cope with it is feasible to find one general solution to cope with various
various complex situations for the complex optimal path computation complex situations. Integrated use of a centralized controller for
in centrally manner in native IP network based on the underlay the more complex optimal path computations in a native IP network
network topology and the real time traffic. results in significant improvements without impacting the underlay
network infrastructure. A proposed solution is described in
[I-D.ietf-teas-pce-native-ip] gives the solution for above scenarios, draft[I-D.ietf-teas-pce-native-ip] .
such thoughts can be extended to cover requirements in other
situations in future.
6. 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. It certainly can protocols and the central control capability of a PCE. While It
ease the management of network in various traffic engineering certainly can ease the management of network in various traffic
scenarios described in this document, but the central control manner engineering scenarios as described in this document, the centralized
also bring the new point that may be easily attacked. Solutions for control also bring a new point that may be easily attacked.
CCDR scenarios should keep these in mind and consider more for the Solutions for CCDR scenarios need to consider protection of the
protection of PCEand their communication with the underlay devices, PCEand communication with the underlay devices. [RFC5440] and
as that described in document [RFC5440] and [RFC8253] [RFC8253] provide additional information.
7. IANA Considerations 7. IANA Considerations
This document does not require any IANA actions. This document does not require any IANA actions.
8. Contributors 8. Contributors
Lu Huang contributes to the content of this draft. Lu Huang contributed to the content of this draft.
9. 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 support and
comments on this draft. comments on this draft.
10. References 10. References
10.1. Normative References 10.1. Normative References
[I-D.ietf-teas-pce-native-ip]
Wang, A., Zhao, Q., Khasanov, B., Chen, H., and R. Mallya,
"PCE in Native IP Network", draft-ietf-teas-pce-native-
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>.
10.2. Informative References 10.2. Informative References
[I-D.ietf-teas-pce-native-ip]
Wang, A., Zhao, Q., Khasanov, B., Chen, H., and R. Mallya,
"PCE in Native IP Network", draft-ietf-teas-pce-native-
ip-03 (work in progress), April 2019.
[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>.
 End of changes. 42 change blocks. 
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