draft-ietf-teas-native-ip-scenarios-09.txt   draft-ietf-teas-native-ip-scenarios-10.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: April 1, 2020 C. Kou Expires: April 11, 2020 C. Kou
BUPT BUPT
Z. Li Z. Li
China Mobile China Mobile
P. Mi P. Mi
Huawei Technologies Huawei Technologies
September 29, 2019 October 9, 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-09 draft-ietf-teas-native-ip-scenarios-10
Abstract Abstract
Requirements for providing the End to End(E2E) performance assurance Requirements for providing the End to End(E2E) performance assurance
are emerging within the service provider network. While there are are emerging within the service provider network. While there are
various technology solutions, there is no one solution which can various technology solutions, there is no one solution which can
fulfill these requirements for a native IP network. One universal fulfill these requirements for a native IP network. One universal
(E2E) solution which can cover both intra-domain and inter-domain (E2E) solution which can cover both intra-domain and inter-domain
scenarios is needed. scenarios is needed.
One feasible E2E traffic engineering solution is the use of a Path One feasible E2E traffic engineering solution is the addition of
Computation Elements (PCE) in a native IP network. This document central control in a native IP network. This document describes
describes various complex scenarios and simulation results when various complex scenarios and simulation results when applying the
applying a PCE in a native IP network. This solution, referred to as Path Computation Element (PCE) in a native IP network. This
Centralized Control Dynamic Routing (CCDR), integrates the advantage solution, referred to as Centralized Control Dynamic Routing (CCDR),
of using distributed protocols and the power of a centralized control integrates the advantage of using distributed protocols and the power
technology. 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-
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Internet-Drafts are draft documents valid for a maximum of six months Internet-Drafts are draft documents valid for a maximum of six months
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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 April 1, 2020. This Internet-Draft will expire on April 11, 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
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Table of Contents Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3 2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. CCDR Scenarios . . . . . . . . . . . . . . . . . . . . . . . 4 3. CCDR Scenarios . . . . . . . . . . . . . . . . . . . . . . . 4
3.1. QoS Assurance for Hybrid Cloud-based Application . . . . 4 3.1. QoS Assurance for Hybrid Cloud-based Application . . . . 4
3.2. Link Utilization Maximization . . . . . . . . . . . . . . 5 3.2. Link Utilization Maximization . . . . . . . . . . . . . . 5
3.3. Traffic Engineering for Multi-Domain . . . . . . . . . . 6 3.3. Traffic Engineering for Multi-Domain . . . . . . . . . . 6
3.4. Network Temporal Congestion Elimination . . . . . . . . . 7 3.4. Network Temporal Congestion Elimination . . . . . . . . . 7
4. CCDR Simulation . . . . . . . . . . . . . . . . . . . . . . . 7 4. CCDR Simulation . . . . . . . . . . . . . . . . . . . . . . . 7
4.1. Case Study . . . . . . . . . . . . . . . . . . . . . . . 7 4.1. Case Study for CCDR algorithm . . . . . . . . . . . . . . 8
4.2. Topology Simulation . . . . . . . . . . . . . . . . . . . 10 4.2. Topology Simulation . . . . . . . . . . . . . . . . . . . 10
4.3. Traffic Matrix Simulation . . . . . . . . . . . . . . . . 10 4.3. Traffic Matrix Simulation . . . . . . . . . . . . . . . . 10
4.4. CCDR End-to-End Path Optimization . . . . . . . . . . . . 11 4.4. CCDR End-to-End Path Optimization . . . . . . . . . . . . 11
4.5. Network Temporal Congestion Elimination . . . . . . . . . 12 4.5. Network Temporal Congestion Elimination . . . . . . . . . 12
5. CCDR Deployment Consideration . . . . . . . . . . . . . . . . 13 5. CCDR Deployment Consideration . . . . . . . . . . . . . . . . 13
6. Security Considerations . . . . . . . . . . . . . . . . . . . 14 6. Security Considerations . . . . . . . . . . . . . . . . . . . 14
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 14 7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 14
8. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 14 8. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 15
9. Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . 14 9. Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . 15
10. References . . . . . . . . . . . . . . . . . . . . . . . . . 14 10. References . . . . . . . . . . . . . . . . . . . . . . . . . 15
10.1. Normative References . . . . . . . . . . . . . . . . . . 14 10.1. Normative References . . . . . . . . . . . . . . . . . . 15
10.2. Informative References . . . . . . . . . . . . . . . . . 15 10.2. Informative References . . . . . . . . . . . . . . . . . 15
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 15 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 16
1. Introduction 1. Introduction
A service provider network is composed of thousands of routers that A service provider network is composed of thousands of routers that
run distributed protocols to exchange the reachability information. run distributed protocols to exchange the reachability information.
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 controlled, by the distributed protocols. These distributed
protocols are robust enough to support most applications, but have protocols are robust enough to support most applications, but have
some difficulties supporting the complexities needed for traffic some difficulties supporting the complexities needed for traffic
engineering applications, e.g. E2E performance assurance, or engineering applications, e.g. E2E performance assurance, or
skipping to change at page 3, line 35 skipping to change at page 3, line 35
Deterministic Networking (DetNet)[RFC8578] is another possible Deterministic Networking (DetNet)[RFC8578] is another possible
solution. It is primarily focused on providing bounded latency for a solution. It is primarily focused on providing bounded latency for a
flow and introduces additional requirements on the domain edge flow and introduces additional requirements on the domain edge
router. The current DetNet scope is within one domain. The use router. The current DetNet scope is within one domain. The use
cases defined in this document do not require the additional cases defined in this document do not require the additional
complexity of deterministic properties and so differ from the DetNet complexity of deterministic properties and so differ from the DetNet
use cases. use cases.
This draft describes scenarios for a native IP network that a This draft describes scenarios for a native IP network that a
Centralized Control Dynamic Routing (CCDR) framework can easily Centralized Control Dynamic Routing (CCDR) framework can easily
solve, without requiring a change of the data plane behaviour on the solve, without requiring a change of the data plane behavior on the
router. It also provides path optimization simulation results to router. It also provides path optimization simulation results to
illustrate the applicability of the CCDR framework. illustrate the applicability of the CCDR framework.
This draft is the base document of the following two drafts: the
universal solution draft, which is suitable for intra-domain and
inter-domain TE scenario, is described in
[I-D.ietf-teas-pce-native-ip]; the related protocol extension
contents is described in [I-D.ietf-pce-pcep-extension-native-ip]
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: Centralized 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
skipping to change at page 4, line 14 skipping to change at page 4, line 20
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 TE: Traffic Engineering
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 various deployment scenarios for The following sections describe various deployment scenarios for
applying the CCDR framework. applying the CCDR framework.
3.1. QoS Assurance for Hybrid Cloud-based Application 3.1. QoS Assurance for Hybrid Cloud-based Application
skipping to change at page 5, line 23 skipping to change at page 5, line 23
| |
//--------------\\ //--------------\\
///// \\\\\ ///// \\\\\
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
As illustrated in Figure 1, the source and destination of the "Cloud
Based Application" traffic are located at "Private Cloud Site" and
"Public Cloud Site" respectively.
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 is determined by the distributed control network. When
applications require the E2E QoS assurance, it can send these application requires the E2E QoS assurance, it can send these
requirements to the PCE, and let the PCE compute one E2E path which requirements to the PCE, and let the PCE compute one E2E path which
is based on the underlying network topology and the real traffic is based on the underlying network topology and the real traffic
information, to accommodate the application's QoS requirements. information, to accommodate the application's QoS requirements.
Section 4 of this document describes the simulation results for this Section 4.4 of this document describes the simulation results for
use case. this use case.
3.2. Link Utilization Maximization 3.2. Link Utilization Maximization
Network topology within a Metro Area Network (MAN) is generally in a Network topology within a Metro Area Network (MAN) is generally in a
star mode as illustrated in Figure 2, with different devices star mode as illustrated in Figure 2, with different devices
connected to different customer types. The traffic from these connected to different customer types. The traffic from these
customers is often in a tidal pattern, with the links between the customers is often in a tidal pattern, with the links between the
Core Router(CR)/Broadband Remote Access Server(BRAS) and CR/Service Core Router(CR)/Broadband Remote Access Server(BRAS) and CR/Service
Router(SR), experiencing congestion in different periods, because the Router(SR), experiencing congestion in different periods, because the
subscribers under BRAS, often use the network at night, and the subscribers under BRAS, often use the network at night, and the
dedicated line users under SR, often use the network during the dedicated line users under SR, often use the network during the
daytime. The uplink between BRAS/SR and CR must satisfy the maximum daytime. The link between BRAS/SR and CR must satisfy the maximum
traffic volume between them respectively and this causes these links traffic volume between them respectively and this causes these links
often to be under-utilized. often to be under-utilized.
+--------+ +--------+
| CR | | CR |
+----|---+ +----|---+
| |
--------|--------|-------| --------|--------|-------|
| | | | | | | |
+--|-+ +-|- +--|-+ +-|+ +--|-+ +-|- +--|-+ +-|+
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+-|-- | ----+ +-|-- | ----+
|IDC|----------------|MAN| |IDC|----------------|MAN|
+---| |---+ +---| |---+
Figure 4: Traffic Engineering for Complex Multi-Domain Topology Figure 4: Traffic Engineering for Complex Multi-Domain Topology
A solution for this scenario requires the gathering of NetFlow A solution for this scenario requires the gathering of NetFlow
information, analysis of the source/destination AS, and determining 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 external Border Gateway Protocol(eBGP) sessions operator can use the external Border Gateway Protocol(eBGP) sessions
to schedule the traffic among the different domains. to schedule the traffic among the different domains according to the
solution described in CCDR framework.
3.4. Network Temporal Congestion Elimination 3.4. Network Temporal Congestion Elimination
In more general situations, there are often temporal congestions In more general situations, there are often temporal congestion
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 methods to often appear repeatedly, and if the service provider has methods to
mitigate it, it will certainly improve their network operations mitigate it, it will certainly improve their network operations
capabilities and increase satisfaction for their customers. CCDR is capabilities and increase satisfaction for their customers. CCDR is
also suitable for such scenarios, as the controller can schedule also suitable for such scenarios, as the controller can schedule
traffic out of the congested links, lowering the utilization of them traffic out of the congested links, lowering the utilization of them
during these times. Section 4 describes the simulation results of during these times. Section 4.5 describes the simulation results of
this scenario. this scenario.
4. CCDR Simulation 4. CCDR Simulation
The following sections describe one case study to illustrate CCDR The following sections describe one case study to illustrate CCDR
algorithm, the topology and traffic matrix generation process and the algorithm, the topology and traffic matrix generation process and the
optimization results for E2E QoS assured path and congestion optimization results for E2E QoS assured path and congestion
elimination in applied scenarios. elimination in applied scenarios.
4.1. Case Study The structure and scale of the simulated topology is similar with the
real network. Several amounts of traffic matrix are generated to
simulate the different congestion condition in network, only one of
them is illustrated.
Figure 5 depicts the topology of the network for the case study. 4.1. Case Study for CCDR algorithm
There are 8 forwarding devices in the network. The original cost and
utilization are marked on it, as shown in the figure. For example,
the original cost and utilization for the link (1,2) are 3 and 50%
respectively. There are two flows: f1 and f2. Both of these two
flows are from node 1 to node 8.For simplicity, it is assumed that
the bandwidth of the link in the network is 10Mb/s.The flow rate of
f1 is 1Mb/s, and the flow rate of f2 is 2Mb/s.The threshold of the
link in congestion is 90%.
If OSPF protocol is applied in the network, which adopts Dijkstra's Figure 5 depicts the topology of the network for the case study of
CCDR algorithm. There are 8 forwarding devices in the network. The
original cost and utilization are marked on it, as shown in the
figure. For example, the original cost and utilization for the link
(1,2) are 3 and 50% respectively. There are two flows: f1 and f2.
Both of these two flows are from node 1 to node 8. For simplicity,
it is assumed that the bandwidth of the link in the network is 10Mb/
s. The flow rate of f1 is 1Mb/s, and the flow rate of f2 is 2Mb/s.
The threshold of the link in congestion is 90%.
If OSPF protocol (ISIS is similar, because it also use the Dijstra's
algorithm) is applied in the network, which adopts Dijkstra's
algorithm, the two flows from node 1 to node 8 can only use the OSPF algorithm, the two flows from node 1 to node 8 can only use the OSPF
path (p1: 1->2->3->8). It is because Dijkstra's algorithm mainly path (p1: 1->2->3->8). It is because Dijkstra's algorithm mainly
considers original cost of the link.Since CCDR considers cost and considers original cost of the link. Since CCDR considers cost and
utilization simultaneously, the same path with OSPF will not be utilization simultaneously, the same path with OSPF will not be
selected due to the severe congestion of the link (2,3). In this selected due to the severe congestion of the link (2,3). In this
case, f1 will select the path (p2: 1->5->6->7->8) since the new cost case, f1 will select the path (p2: 1->5->6->7->8) since the new cost
of this path is better than that of OSPF path.Moreover, the path p2 of this path is better than that of OSPF path. Moreover, the path p2
is also better than the path (p3: 1->2->4->7->8) for for flow f1. is also better than the path (p3: 1->2->4->7->8) for for flow f1.
However,f2 will not select the same path since it will cause the new However, f2 will not select the same path since it will cause the new
congestion in the link (6,7). As a result, f2 will select the path congestion in the link (6,7). As a result, f2 will select the path
(p3: 1->2->4->7->8). (p3: 1->2->4->7->8).
+-------+ +-------+ +-------+ +-------+
+---------+ f1 +--------->| | ----------> | | +---------+ f1 +--------->| | ----------> | |
| |---------------+ | +--------| 3 |-------------| 8 | | |---------------+ | +--------| 3 |-------------| 8 |
|Edge Node|-------------+ | | | +----->| | ----------> | | |Edge Node|-------------+ | | | +----->| | ----------> | |
| | | | | | | +-------+ 6/50% +-------+ | | | | | | | +-------+ 6/50% +-------+
+---------+ | | 4/95% | | | | +---------+ | | 4/95% | | | |
| | | | | 5/60% | | | | | | 5/60% |
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|Edge Node|-------| 1 |---------- | 2 |---------| 4 |--------| 7 | |Edge Node|-------| 1 |---------- | 2 |---------| 4 |--------| 7 |
| |-----> | |---------> | | 7/60% | | 5/45% | | | |-----> | |---------> | | 7/60% | | 5/45% | |
+---------+ f2 +-------+ 3/50% +-------+ +-------+ +-------+ +---------+ f2 +-------+ 3/50% +-------+ +-------+ +-------+
| | | |
| | | |
| +-------+ +-------+ | | +-------+ +-------+ |
| 3/60% | | 5/55% | | 3/75%| | 3/60% | | 5/55% | | 3/75%|
+---------------| 5 |-----------| 6 |----------+ +---------------| 5 |-----------| 6 |----------+
| | | | | | | |
+-------+ +-------+ +-------+ +-------+
(a) Dijkstra's Algorithm (a) Dijkstra's Algorithm(OSPF/ISIS)
+-------+ +-------+ +-------+ +-------+
+---------+ f1 | | | | +---------+ f1 | | | |
| |---------------+ +--------| 3 |-------------| 8 | | |---------------+ +--------| 3 |-------------| 8 |
|Edge Node|-------------+ | | | | | | |Edge Node|-------------+ | | | | | |
| | | | | +-------+ 6/50% +-------+ | | | | | +-------+ 6/50% +-------+
+---------+ | | 4/95%| ^ | ^ +---------+ | | 4/95%| ^ | ^
| | | 5/60% | | | | | | 5/60% | | |
| v | | | | | v | | | |
+---------+ +-------+ +-------+ +-------+ +-------+ +---------+ +-------+ +-------+ +-------+ +-------+
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+---------+ f2 +-------+ 3/50% +-------+ +-------+ +-------+ +---------+ f2 +-------+ 3/50% +-------+ +-------+ +-------+
| | | ^ | | | ^
| | | | | | | |
| | +-------+ +-------+ | | | | +-------+ +-------+ | |
| | 3/60% | | 5/55% | | 3/75%| | | | 3/60% | | 5/55% | | 3/75%| |
| +---------------| 5 |-----------| 6 |----------+ | | +---------------| 5 |-----------| 6 |----------+ |
+--------------> | |---------> | |------------+ +--------------> | |---------> | |------------+
+-------+ +-------+ +-------+ +-------+
(b) CCDR Algorithm (b) CCDR Algorithm
Figure 5: Case Study Figure 5: Case Study for CCDR's Algorithm
4.2. Topology Simulation 4.2. Topology Simulation
The network topology mainly contains nodes and links information. The network topology mainly contains nodes and links information.
Nodes used in the 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 6 is a topology connected only with some of the core nodes. Figure 6 is a topology
example of 4 core nodes and 5 edge nodes. In this CCDR simulation, example of 4 core nodes and 5 edge nodes. In this CCDR simulation,
100 core nodes and 400 edge nodes are generated. 100 core nodes and 400 edge nodes are generated.
skipping to change at page 12, line 42 skipping to change at page 12, line 42
| *| | *|
| * *| | * *|
| * * * * * ** * *| | * * * * * ** * *|
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 7: Simulation Result with Congestion Elimination Figure 7: Simulation Result with Congestion Elimination
4.5. Network Temporal Congestion Elimination 4.5. Network Temporal Congestion Elimination
Different degrees of network congestions were simulated. The Different degrees of network congestion 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 8. The CCDR congestion elimination performance is shown in Figure 8.
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 8 is the CD about 20%. The second graph shown in Figure 8 is the CD distribution
distribution after using the congestion elimination process. It after using the congestion elimination process. It shows only 12
shows only 12 links among totally 20000 links exceed the threshold, links among totally 20000 links exceed the threshold, and all the CD
and all the CD values are less than 3%. Thus, after scheduling of the values are less than 3%. Thus, after scheduling of the traffic away
traffic away from the congested paths, the degree of network from the congested paths, the degree of network congestion is greatly
congestion is greatly eliminated and the network utilization is in eliminated and the network utilization is in balance.
balance.
Before congestion elimination Before congestion elimination
+-----------------------------------------------------------+ +-----------------------------------------------------------+
| * ** * ** ** *| | * ** * ** ** *|
20| * * **** * ** ** *| 20| * * **** * ** ** *|
|* * ** * ** ** **** * ***** *********| |* * ** * ** ** **** * ***** *********|
|* * * * * **** ****** * ** *** **********************| |* * * * * **** ****** * ** *** **********************|
15|* * * ** * ** **** ********* *****************************| 15|* * * ** * ** **** ********* *****************************|
|* * ****** ******* ********* *****************************| |* * ****** ******* ********* *****************************|
CD(%) |* ********* ******* ***************************************| CD(%) |* ********* ******* ***************************************|
skipping to change at page 13, line 46 skipping to change at page 13, 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 8: Simulation Result with Congestion Elimination Figure 8: Simulation Result with Congestion Elimination
More detailed information about the algorithm can refer to [PTCS] .
5. CCDR Deployment Consideration 5. CCDR Deployment Consideration
With the above CCDR scenarios and simulation results, we demonstrate Above CCDR scenarios and simulation results demonstrate that it is
it is feasible to find one general solution to cope with various feasible to find one general solution to cope with various complex
complex situations. Integrated use of a centralized controller for situations. Integrated use of a centralized controller for the more
the more complex optimal path computations in a native IP network complex optimal path computations in a native IP network results in
results in significant improvements without impacting the underlay significant improvements without impacting the underlay network
network infrastructure. A proposed solution is described in infrastructure.
draft[I-D.ietf-teas-pce-native-ip] .
More detailed information about the algorithm can refer to the IEEE For intra-domain or inter-domain native IP TE scenario, the
document " A Practical Traffic Control Scheme With Load Balancing deployment of CCDR solution is similar. This universal deployment
Based on PCE Architecture" characteristic can facilitate the operator to tackle their traffic
engineering issues in one general manner. To deploy the CCDR
solution, the PCE should collect the underlay network topology
dynamically, for example via BGP-LS[RFC7752]. It also needs to
gather the network traffic information periodically from the network
management platform. The simulation results show PCE can compute the
E2E optimal path within seconds thus it can cope with the change of
underlay network in minute scale. More agile requirements needs
increase the sample rate of underlay network, also decrease the
detection and notification interval of underlay network. The methods
to gather and decrease the latency of these information are out of
the scope of this draft.
6. Security Considerations 6. Security Considerations
This document considers mainly the integration of distributed This document considers mainly the integration of distributed
protocols and the central control capability of a PCE. While It protocols and the central control capability of a PCE. While it
certainly can ease the management of network in various traffic certainly can ease the management of network in various traffic
engineering scenarios as described in this document, the centralized engineering scenarios as described in this document, the centralized
control also bring a new point that may be easily attacked. control also bring a new point that may be easily attacked.
Solutions for CCDR scenarios need to consider protection of the PCE Solutions for CCDR scenarios need to consider protection of the PCE
and communication with the underlay devices. [RFC5440] and [RFC8253] and communication with the underlay devices.
provide additional information.
[RFC5440] and [RFC8253] provide additional information.
The control priority and interaction process should also be carefully
designed for the combination of distributed protocol and central
control. Generally, the central control instruction should have
higher priority than the forwarding actions determined by the
distributed protocol. When the communication between PCE and the
underlay devices is not in function, the distributed protocol should
take over the control right of the underlay network.
[I-D.ietf-teas-pce-native-ip] provide more considerations
corresponding to the solution.
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 contributed 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 support and Huaimo Chen, Vishnu Beeram and Lou Berger for their support and
comments on this draft. comments on this draft.
Thanks Benjamin Kaduk, Roman Danyliw, Alvaro Retana and Eric Vyncke
for their views and comments.
10. References 10. References
10.1. Normative References 10.1. Normative References
[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>.
[RFC7752] Gredler, H., Ed., Medved, J., Previdi, S., Farrel, A., and
S. Ray, "North-Bound Distribution of Link-State and
Traffic Engineering (TE) Information Using BGP", RFC 7752,
DOI 10.17487/RFC7752, March 2016,
<https://www.rfc-editor.org/info/rfc7752>.
[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-pce-pcep-extension-native-ip]
Wang, A., Khasanov, B., Cheruathur, S., Zhu, C., and S.
Fang, "PCEP Extension for Native IP Network", draft-ietf-
pce-pcep-extension-native-ip-04 (work in progress), August
2019.
[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-04 (work in progress), August 2019. ip-04 (work in progress), August 2019.
[PTCS] Zhang, P., Xie, K., Kou, C., Huang, X., Wang, A., and Q.
Sun, "A Practical Traffic Control Scheme With Load
Balancing Based on PCE Architecture", IEEE
Access 18526773, DOI 10.1109/ACCESS.2019.2902610, March
2019, <http://ieeexplore.ieee.org/document/8657733>.
[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>.
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