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Versions: (draft-wang-teas-ccdr) 00 01 02 03 04 05 06

TEAS Working Group                                               A. Wang
Internet-Draft                                             China Telecom
Intended status: Informational                                  X. Huang
Expires: January 2, 2020                                          C. Kou
                                                                    BUPT
                                                                   Z. Li
                                                            China Mobile
                                                                   P. Mi
                                                     Huawei Technologies
                                                            July 1, 2019


      Scenarios and Simulation Results of PCE in Native IP Network
                 draft-ietf-teas-native-ip-scenarios-06

Abstract

   This document describes the scenarios and simulation results for PCE
   in native IP network, which integrates the merit of distributed
   protocols (IGP/BGP), and the power of centrally control technologies
   (PCE/SDN) to provide one feasible traffic engineering solution in
   various complex scenarios for the service provider.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
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   This Internet-Draft will expire on January 2, 2020.

Copyright Notice

   Copyright (c) 2019 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   (https://trustee.ietf.org/license-info) in effect on the date of



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   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  CCDR Scenarios. . . . . . . . . . . . . . . . . . . . . . . .   3
     2.1.  QoS Assurance for Hybrid Cloud-based Application. . . . .   3
     2.2.  Link Utilization Maximization . . . . . . . . . . . . . .   4
     2.3.  Traffic Engineering for Multi-Domain  . . . . . . . . . .   5
     2.4.  Network Temporal Congestion Elimination.  . . . . . . . .   6
   3.  CCDR Simulation.  . . . . . . . . . . . . . . . . . . . . . .   6
     3.1.  Topology Simulation . . . . . . . . . . . . . . . . . . .   6
     3.2.  Traffic Matrix Simulation.  . . . . . . . . . . . . . . .   7
     3.3.  CCDR End-to-End Path Optimization . . . . . . . . . . . .   7
     3.4.  Network Temporal Congestion Elimination . . . . . . . . .   9
   4.  CCDR Deployment Consideration.  . . . . . . . . . . . . . . .  10
   5.  Security Considerations . . . . . . . . . . . . . . . . . . .  11
   6.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  11
   7.  Contributors  . . . . . . . . . . . . . . . . . . . . . . . .  11
   8.  Acknowledgement . . . . . . . . . . . . . . . . . . . . . . .  11
   9.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  11
     9.1.  Normative References  . . . . . . . . . . . . . . . . . .  11
     9.2.  Informative References  . . . . . . . . . . . . . . . . .  12
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  12

1.  Introduction

   Service provider network is composed thousands of routers that run
   distributed protocol to exchange the reachability information between
   them.  The path for the destination network is mainly calculated and
   controlled by the IGP/BGP protocols.  These distributed protocols are
   robust enough to support the current evolution of Internet but have
   some difficulties when application requires the end-to-end QoS
   performance, or in the situation that the service provider wants to
   maximize the link utilization within their network.

   MPLS-TE technology [RFC3209]is one solution for finely planned
   network but it will put heavy burden on the routers when we use it to
   meet the dynamic QoS assurance requirements within real time traffic
   network.

   SR(Segment Routing) [RFC8402] is another solution that integrates
   some merits of distributed protocol and the advantages of centrally



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   control mode, but it requires the underlying network, especially the
   provider edge router to do label push and pop action in-depth, and
   need complex mechanic for coexisting with the Non-SR network.
   Additionally, it can only maneuver the end-to-end path for MPLS and
   IPv6 traffic via different mechanisms.

   DetNet[RFC8578] describes use cases for diverse industries that have
   a common need for "deterministic flows", which can provide guaranteed
   bandwidth, bounded latency, and other properties germane to the
   transport of time-sensitive data.  The use cases focus mainly on the
   industrial critical applications within one centrally controlled
   network and are out of scope of this draft.

   This draft describes scenarios that the centrally control dynamic
   routing (CCDR) framework can easily solve, without the change of the
   data plane behaviour on the router.  It also gives the path
   optimization simulation results to illustrate the applicability of
   CCDR framework.

2.  CCDR Scenarios.

   The following sections describe some scenarios that the CCDR
   framework is suitable for deployment.

2.1.  QoS Assurance for Hybrid Cloud-based Application.

   With the emerge of cloud computing technologies, enterprises are
   putting more and more services on the public oriented cloud
   environment, but keep core business within their private cloud.  The
   communication between the private and public cloud sites will span
   the WAN network.  The bandwidth requirements between them are
   variable and the background traffic between these two sites changes
   from time to time.  Enterprise applications just want to exploit the
   network capabilities to assure the end-to-end QoS performance on
   demand.

   CCDR, which integrates the merits of distributed protocol and the
   power of centrally control, is suitable for this scenario.  The
   possible solution framework is illustrated below:












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                            +------------------------+
                            | Cloud Based Application|
                            +------------------------+
                                        |
                                  +-----------+
                                  |    PCE    |
                                  +-----------+
                                        |
                                        |
                               //--------------\\
                          /////                  \\\\\
     Private Cloud Site ||       Distributed          |Public Cloud Site
                         |       Control Network      |
                          \\\\\                  /////
                               \\--------------//

                  Fig.1 Hybrid Cloud Communication Scenario

   By default, the traffic path between the private and public cloud
   site will be determined by the distributed control network.  When
   applications require the end-to-end QoS assurance, it can send these
   requirements to PCE,let PCE compute one e2e path which is based on
   the underlying network topology and the real traffic information, to
   accommodate the application's QoS requirements.  The proposed
   solution can refer the draft [I-D.ietf-teas-pce-native-ip].
   Section 4 describes the detail simulation process and the result.

2.2.  Link Utilization Maximization

   Network topology within MAN is generally in star mode as illustrated
   in Fig.2, with different devices connect different customer types.
   The traffic from these customers is often in tidal pattern that the
   links between the CR/BRAS and CR/SR will experience congestion in
   different periods, because the subscribers under BRAS often use the
   network at night and the dedicated line users under SR often use the
   network during the daytime.  The uplink between BRAS/SR and CR must
   satisfy the maximum traffic volume between them respectively and this
   causes these links often in underutilization situation.













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                              +--------+
                              |   CR   |
                              +----|---+
                                   |
                       --------|--------|-------|
                       |       |        |       |
                    +--|-+   +-|-    +--|-+   +-|+
                    |BRAS|   |SR|    |BRAS|   |SR|
                    +----+   +--+    +----+   +--+

              Fig.2 Star-mode Network Topology within MAN

   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
   exploit the tidal phenomena between BRAS/CR and SR/CR links, maximize
   the links (which is more expensive) utilization of them .

                                       +-------+
                                   -----  PCE  |
                                   |   +-------+
                              +----|---+
                              |   CR   |
                              +----|---+
                                   |
                       --------|--------|-------|
                       |       |        |       |
                    +--|-+   +-|-    +--|-+   +-|+
                    |BRAS-----SR|    |BRAS-----SR|
                    +----+   +--+    +----+   +--+

                   Fig.3 Link Utilization Maximization via CCDR

2.3.  Traffic Engineering for Multi-Domain

   Operator's networks are often comprised by different domains,
   interconnected with each other,form very complex topology that
   illustrated in Fig.4.  Due to the traffic pattern to/from MAN and
   IDC, the utilization of links between them are often asymmetric.  It
   is almost impossible to balance the utilization of these links via
   the distributed protocol, but this unbalance phenomenon can be
   overcome via the CCDR framework.










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                    +---+                +---+
                    |MAN|-----------------IDC|
                    +-|-|       |        +-|-+
                      |     ---------|     |
                      ------|BackBone|------
                      |     ----|----|     |
                      |         |          |
                    +-|--       |        ----+
                    |IDC|----------------|MAN|
                    +---|                |---+

        Fig.4 Traffic Engineering for Complex Multi-Domain Topology

   Solution for this scenario requires the gather of NetFlow
   information, analysis the source/destination AS of them and determine
   which pair is the main cause of the congested link.  After this, the
   operator can use the multi eBGP sessions described in
   [I-D.ietf-teas-pce-native-ip]to schedule the traffic among different
   domains.

2.4.  Network Temporal Congestion Elimination.

   In more general situation, there are often temporal congestions
   within the service provider's network.  Such congestion phenomena
   often appear repeatedly and if the service provider has some methods
   to mitigate it, it will certainly increase the degree of satisfaction
   for their customers.  CCDR is also suitable for such scenario in such
   manner that the distributed protocol process most of the traffic
   forwarding and the controller schedule some traffic out of the
   congestion links to lower the utilization of them.  Section 4
   describes the simulation process and results about such scenario.

3.  CCDR Simulation.

   The following sections describe the topology, traffic matrix, end-to-
   end path optimization and congestion elimination in CCDR applied
   scenarios.

3.1.  Topology Simulation

   The network topology mainly contains nodes and links information.
   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
   connected only with some of the core nodes.  Fig.5 is a topology
   example of 4 core nodes and 5 edge nodes.  In CCDR simulation, 100
   core nodes and 400 edge nodes are generated.





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                                     +----+
                                    /|Edge|\
                                   | +----+ |
                                   |        |
                                   |        |
                     +----+    +----+     +----+
                     |Edge|----|Core|-----|Core|---------+
                     +----+    +----+     +----+         |
                             /  |    \   /   |           |
                       +----+   |     \ /    |           |
                       |Edge|   |      X     |           |
                       +----+   |     / \    |           |
                             \  |    /   \   |           |
                     +----+    +----+     +----+         |
                     |Edge|----|Core|-----|Core|         |
                     +----+    +----+     +----+         |
                                 |          |            |
                                 |          +------\   +----+
                                 |                  ---|Edge|
                                 +-----------------/   +----+


                        Fig.5 Topology of Simulation

   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
   than 20000.  Each link has its congestion threshold.

3.2.  Traffic Matrix Simulation.

   The traffic matrix is generated based on the link capacity of
   topology.  It can result in many kinds of situations, such as
   congestion, mild congestion and non-congestion.

   In CCDR simulation, the dimension of the traffic matrix is 500*500.
   About 20% links are overloaded when the Open Shortest Path First
   (OSPF) protocol is used in the network.

3.3.  CCDR End-to-End Path Optimization

   The CCDR end-to-end 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 threshold.  Based on the current state of the network, PCE
   within CCDR framework combines the shortest path algorithm with
   penalty theory of classical optimization and graph theory.

   Given background traffic matrix which is unscheduled, when a set of
   new flows comes into the network, the end-to-end path optimization



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   finds the optimal paths for them.  The selected paths bring the least
   congestion degree to the network.

   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
   is the UID with OSPF and the second graph is the UID with CCDR end-
   to-end path optimization.  The average UID of the first graph is more
   than 30%. After path optimization, the average UID is less than 5%.
   The results show that the CCDR end-to-end path optimization has an
   eye-catching decreasing in UID relative to the path chosen based on
   OSPF.

           +-----------------------------------------------------------+
           |                *                               *    *    *|
         60|                *                             * * *  *    *|
           |*      *       **     * *         *   *   *  ** * *  * * **|
           |*   * ** *   * **   *** **  *   * **  * * *  ** * *  *** **|
           |* * * ** *  ** **   *** *** **  **** ** ***  **** ** *** **|
         40|* * * ***** ** ***  *** *** **  **** ** *** ***** ****** **|
     UID(%)|* * ******* ** ***  *** ******* **** ** *** ***** *********|
           |*** ******* ** **** *********** *********** ***************|
           |******************* *********** *********** ***************|
         20|******************* ***************************************|
           |******************* ***************************************|
           |***********************************************************|
           |***********************************************************|
          0+-----------------------------------------------------------+
          0    100   200   300   400   500   600   700   800   900  1000
           +-----------------------------------------------------------+
           |                                                           |
         60|                                                           |
           |                                                           |
           |                                                           |
           |                                                           |
         40|                                                           |
     UID(%)|                                                           |
           |                                                           |
           |                                                           |
         20|                                                           |
           |                                                          *|
           |                                     *                    *|
           |        *         *  *    *       *  **                 * *|
          0+-----------------------------------------------------------+
          0    100   200   300   400   500   600   700   800   900  1000
                                Flow Number
             Fig.6 Simulation Result with Congestion Elimination





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3.4.  Network Temporal Congestion Elimination

   Different degree of network congestions are simulated.  The
   congestion degree (CD) is defined as the link utilization beyond its
   threshold.

   The CCDR congestion elimination performance is shown in Fig.7.  The
   first graph is the congestion degree before the process of congestion
   elimination.  The average CD of all congested links is more than 10%.
   The second graph shown in Fig.7 is the congestion degree after
   congestion elimination process.  It shows only 12 links among totally
   20000 links exceed the threshold, and all the congestion degree is
   less than 3%. Thus, after scheduling of the traffic in congestion
   paths, the degree of network congestion is greatly eliminated and the
   network utilization is in balance.




































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                          Before congestion elimination
           +-----------------------------------------------------------+
           |                *                            ** *   ** ** *|
         20|                *                     *      **** * ** ** *|
           |*      *       **     * **       **  **** * ***** *********|
           |*   *  * *   * **** ****** *  ** *** **********************|
         15|* * * ** *  ** **** ********* *****************************|
           |* * ******  ******* ********* *****************************|
     CD(%) |* ********* ******* ***************************************|
         10|* ********* ***********************************************|
           |*********** ***********************************************|
           |***********************************************************|
          5|***********************************************************|
           |***********************************************************|
           |***********************************************************|
          0+-----------------------------------------------------------+
              0            0.5            1            1.5            2

                        After congestion elimination
          +-----------------------------------------------------------+
          |                                                           |
        20|                                                           |
          |                                                           |
          |                                                           |
        15|                                                           |
          |                                                           |
    CD(%) |                                                           |
        10|                                                           |
          |                                                           |
          |                                                           |
        5 |                                                           |
          |                                                           |
          |        *        **  * *  *  **   *  **                 *  |
        0 +-----------------------------------------------------------+
           0            0.5            1            1.5            2
                            Link Number(*10000)
            Fig.7 Simulation Result with Congestion Elimination

4.  CCDR Deployment Consideration.

   With the above CCDR scenarios and simulation results, we can know it
   is necessary and feasible to find one general solution to cope with
   various complex situations for the complex optimal path computation
   in centrally manner based on the underlay network topology and the
   real time traffic.






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   [I-D.ietf-teas-pce-native-ip] gives the solution for above scenarios,
   such thoughts can be extended to cover requirements in other
   situations in future.

5.  Security Considerations

   This document considers mainly the integration of distributed
   protocol and the central control capability of PCE/SDN.  It certainly
   can ease the management of network in various traffic-engineering
   scenarios described in this document, but the central control manner
   also bring the new point that may be easily attacked.  Solutions for
   CCDR scenarios should keep these in mind and consider more for the
   protection of PCE/SDN controller and their communication with the
   underlay devices, as that described in document [RFC5440] and
   [RFC8253]

6.  IANA Considerations

   This document does not require any IANA actions.

7.  Contributors

   Lu Huang contributes to the content of this draft.

8.  Acknowledgement

   The author would like to thank Deborah Brungard, Adrian Farrel,
   Huaimo Chen, Vishnu Beeram and Lou Berger for their supports and
   comments on this draft.

9.  References

9.1.  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
              Element (PCE) Communication Protocol (PCEP)", RFC 5440,
              DOI 10.17487/RFC5440, March 2009,
              <https://www.rfc-editor.org/info/rfc5440>.








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   [RFC8253]  Lopez, D., Gonzalez de Dios, O., Wu, Q., and D. Dhody,
              "PCEPS: Usage of TLS to Provide a Secure Transport for the
              Path Computation Element Communication Protocol (PCEP)",
              RFC 8253, DOI 10.17487/RFC8253, October 2017,
              <https://www.rfc-editor.org/info/rfc8253>.

9.2.  Informative References

   [RFC3209]  Awduche, D., Berger, L., Gan, D., Li, T., Srinivasan, V.,
              and G. Swallow, "RSVP-TE: Extensions to RSVP for LSP
              Tunnels", RFC 3209, DOI 10.17487/RFC3209, December 2001,
              <https://www.rfc-editor.org/info/rfc3209>.

   [RFC8402]  Filsfils, C., Ed., Previdi, S., Ed., Ginsberg, L.,
              Decraene, B., Litkowski, S., and R. Shakir, "Segment
              Routing Architecture", RFC 8402, DOI 10.17487/RFC8402,
              July 2018, <https://www.rfc-editor.org/info/rfc8402>.

   [RFC8578]  Grossman, E., Ed., "Deterministic Networking Use Cases",
              RFC 8578, DOI 10.17487/RFC8578, May 2019,
              <https://www.rfc-editor.org/info/rfc8578>.

Authors' Addresses

   Aijun Wang
   China Telecom
   Beiqijia Town, Changping District
   Beijing, Beijing  102209
   China

   Email: wangaj.bri@chinatelecom.cn


   Xiaohong Huang
   Beijing University of Posts and Telecommunications
   No.10 Xitucheng Road, Haidian District
   Beijing
   China

   Email: huangxh@bupt.edu.cn











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   Caixia Kou
   Beijing University of Posts and Telecommunications
   No.10 Xitucheng Road, Haidian District
   Beijing
   China

   Email: koucx@lsec.cc.ac.cn


   Zhenqiang Li
   China Mobile
   32 Xuanwumen West Ave, Xicheng District
   Beijing  100053
   China

   Email: li_zhenqiang@hotmail.com


   Penghui Mi
   Huawei Technologies
   Tower C of Bldg.2, Cloud Park, No.2013 of Xuegang Road
   Shenzhen, Bantian,Longgang District  518129
   China

   Email: mipenghui@huawei.com


























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