TEAS Working Group A.Wang Internet Draft China Telecom Xiaohong Huang BUPT Caixia Kou BUPT Lu Huang China Mobile Penghui Mi Tencent Company Intended status: Information Track July 18, 2017 Expires: January 17, 2018 CCDR Scenario, Simulation and Suggestion draft-wang-teas-ccdr-01.txt Status of this Memo This Internet-Draft is submitted in full conformance with the provisions of BCP 78 and BCP 79. This Internet-Draft is submitted in full conformance with the provisions of BCP 78 and BCP 79. This document may not be modified, and derivative works of it may not be created, and it may not be published except as an Internet-Draft. This Internet-Draft is submitted in full conformance with the provisions of BCP 78 and BCP 79. This document may not be modified, and derivative works of it may not be created, except to publish it as an RFC and to translate it into languages other than English. it for publication as an RFC or to translate it into languages other than English. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF), its areas, and its working groups. Note that other groups may also distribute working documents as Internet- Drafts. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress." The list of current Internet-Drafts can be accessed at http://www.ietf.org/ietf/1id-abstracts.txt Expires January 17, 2018 [Page 1] Internet-Draft CCDR Scenario, Simulation and Suggestion July 18, 2017 The list of Internet-Draft Shadow Directories can be accessed at http://www.ietf.org/shadow.html This Internet-Draft will expire on January 18, 2009. Copyright Notice Copyright (c) 2017 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 (http://trustee.ietf.org/license-info) in effect on the date of publication of this document. Please review these documents carefully, as they describe your rights and restrictions with respect to this document. Abstract This document describes the scenarios, simulation and suggestions for the "Centrally Control Dynamic Routing (CCDR)" architecture, which integrates the merit of traditional 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. Traditional MPLS-TE solution is mainly used in static network planning scenario and is difficult to meet the QoS assurance requirements in real-time traffic network. With the emerge of SDN concept and related technologies, it is possible to simplify the complexity of distributed control protocol, utilize the global view of network condition, give more efficient solution for traffic engineering in various complex scenarios. Table of Contents 1. Introduction ................................................ 3 2. Conventions used in this document............................ 4 3. CCDR Scenarios. ............................................. 4 3.1. Qos Assurance for Hybrid Cloud-based Application.........4 3.2. Increase link utilization based on tidal phenomena.......5 3.3. Traffic engineering for IDC/MAN asymmetric link..........6 3.4. Network temporal congestion elimination. ................6 4. CCDR Simulation. ............................................ 7 4.1. Topology Simulation..................................... 7 4.2. Traffic Matrix Simulation............................... 8 4.3. End-to-End Path Optimization............................ 8 4.4. Network temporal congestion elimination .................9 Expires January 17, 2018 [Page 2] Internet-Draft CCDR Scenario, Simulation and Suggestion July 18, 2017 5. CCDR Deployment Consideration............................... 11 6. Security Considerations..................................... 11 7. IANA Considerations ........................................ 11 8. Conclusions ................................................ 11 9. References ................................................. 11 9.1. Normative References................................... 11 9.2. Informative References................................. 12 10. Contributors: ............................................. 12 11. Acknowledgments ........................................... 13 1. Introduction Internet network is composed mainly tens of 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 traditional IGP protocol. These distributed protocols are robust enough to support the current evolution of Internet but has some difficulties when the application requires the end-to-end QoS performance, or the service provider wants to maximize the links utilization within their network. MPLS-TE technology is one perfect solution for the finely planned network but it will put heavy burden on the router when we use it to solve the dynamic QoS assurance requirements within real time traffic network. SR(Segment Routing) is another prominent solution that integrates some merits of traditional distributed protocol and the advantages of centrally control mode, but it requires the underlying network, especially the provider edge router to do label push and pop action in-depth, and need some complex solutions for co-exist with the Non- SR network. Finally, it can only maneuver the end-to-end path for MPLS and IPv6 traffic via different mechanism. The advantage of MPLS is mainly for traffic isolation, such as the L2/L3 VPN service deployments. With the emerge of cloud-based services, especially the hybrid cloud communication services, the customers requires mainly the end-to-end QoS assurance services between their private infrastructure and the rented public servers. Without the help of centrally control architecture, the service provider almost can't make such SLA guarantees upon the real time traffic situation. This draft gives some scenarios that the centrally control dynamic Expires January 17, 2018 [Page 3] Internet-Draft CCDR Scenario, Simulation and Suggestion July 18, 2017 routing (CCDR) architecture can easily solve, without adding more extra burdening on the router. It also gives the PCE algorithm results under the similar topology, traffic pattern and network size to illustrate the applicability of CCDR architecture. Finally, it gives some suggestions for the implementation and deployment of CCDR. 2. Conventions used in this document The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in RFC 2119 [RFC2119]. 3. CCDR Scenarios. The following sections describe some scenarios that the CCDR architecture is suitable for deployment. 3.1. 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 service infrastructure, but keep still some core services within their network. The bandwidth requirements between the private cloud and the public cloud are occasionally and the background traffic between these two sites varied from time to time. Enterprise cloud applications just want to have the capabilities to invoke the network to make the end-to-end QoS assurance on demand. Otherwise, the traffic should be controlled by the default distributed protocol. CCDR, which integrates the merits of distributed protocol and the power of centrally control, is suitable for this scenario. The possible solution architecture is illustrated below: +------------------------+ | Cloud Based Application| +------------------------+ | +-----------+ | PCE | +-----------+ | | //--------------\\ ///// \\\\\ Private Cloud Site || Distributed |Public Cloud Site | Control Network | \\\\\ ///// \\--------------// Expires January 17, 2018 [Page 4] Internet-Draft CCDR Scenario, Simulation and Suggestion July 18, 2017 Fig.1 Hybrid Cloud Communication Scenario By default, the traffic path between the private cloud site and public cloud site will be determined by the distributed control network. When some 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 bandwidth requirements. The proposed solution can refer the draft [draft-wang- teas-pce-native-ip]. Section 4 describes the detail simulation process and the results. 3.2. Increase link utilization based on tidal phenomena. Currently, the network topology within MAN is generally in star style as illustrated in Fig.2, with the different devices connect different kind customer. The traffic pattern of these customers demonstrates some tidal phenomena 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 pattern between them and this causes the links utilization always not efficient enough. +--------+ | CR | +----|---+ | --------|--------|-------| | | | | +--|-+ +-|- +--|-+ +-|+ |BRAS| |SR| |BRAS| |SR| +----+ +--+ +----+ +--+ Fig.2 STAR-style network topology within MAN If we can consider link the BRAS/SR with local loop, and control the MAN with the CCDR architecture, we can exploit the tidal phenomena between BRAS/CR and SR/CR links, increase the efficiency of them. +-------+ ----- PCE | | +-------+ +----|---+ | CR | +----|---+ | --------|--------|-------| Expires January 17, 2018 [Page 5] Internet-Draft CCDR Scenario, Simulation and Suggestion July 18, 2017 | | | | +--|-+ +-|- +--|-+ +-|+ |BRAS-----SR| |BRAS-----SR| +----+ +--+ +----+ +--+ Fig.3 Increase the link utilization via CCDR 3.3. Traffic engineering for IDC/MAN asymmetric link The operator's networks are often comprised by tens of 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 links between them are often in asymmetric style. It is almost impossible to balance the utilization of these links via the traditional distributed protocol, but this unbalance phenomenon can be overcome via the CCDR architecture. +---+ +---+ |MAN|-----------------IDC| +-|-| | +-|-+ | ---------| | ------|BackBone|------ | ----|----| | | | | +-|-- | ----+ |IDC|----------------|MAN| +---| |---+ Fig.4 TE within Complex Multi-Domain topology 3.4. Network temporal congestion elimination. In more general situation, there are often temporal congestion periods within part of the service provider's network. Such congestion phenomena will appear repeatedly and if the service provider has some methods to mitigate it, it will certainly increase the satisfaction degree of their customer. CCDR is also suitable for such scenario that the traditional distributed protocol will process most of the traffic forwarding and the controller will 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. Expires January 17, 2018 [Page 6] Internet-Draft CCDR Scenario, Simulation and Suggestion July 18, 2017 4. CCDR Simulation. The following sections describe the topology, traffic matrix, end- to-end path optimization and congestion elimination in CCDR simulation. 4.1. Topology Simulation. Technically, the topology involved nodes and links state information is significantly helpful for traffic schedule. The network topology mainly contains nodes and links information. Nodes used in simulation have two types: core nodes and edge nodes. The core nodes are fully linked to each other. The edge nodes are connected with some of the core nodes. And edge nodes are not connected with other edge nodes directly. Fig.5 is a topology example of 4 core nodes and 5 edge nodes. In this simulation, 100 core nodes and 400 edge nodes are generated. +----+ /|Edge|\ | +----+ | | | | | +----+ +----+ +----+ |Edge|----|Core|-----|Core|---------+ +----+ +----+ +----+ | / | \ / | | +----+ | \ / | | |Edge| | X | | +----+ | / \ | | \ | / \ | | +----+ +----+ +----+ | |Edge|----|Core|-----|Core| | +----+ +----+ +----+ | | | | | +------\ +----+ | ---|Edge| +-----------------/ +----+ Fig.5 Topology of simulation The total number of links is set to be more than 20000. The number of links connecting one edge node to the set of core nodes is randomly between 2 to 30. The bandwidth of all links is set to be 100Gbps. The metric of links between core nodes themselves is set to be from 60 to 100, while metric of links between core nodes and edge nodes is set to be from 1000 to 1060. The metric of links is used Expires January 17, 2018 [Page 7] Internet-Draft CCDR Scenario, Simulation and Suggestion July 18, 2017 for selecting the shortest paths of all source-destination pairs. Besides, each link has its congestion threshold. For the links between core nodes, the threshold is set to be 0.8 which means when its utilization is beyond 80% the link is overloaded. Otherwise, the link is not congested. Similarly, the threshold of links between an edge node and a core node is set to be 0.9. 4.2. Traffic Matrix Simulation. The end-to-end traffic of the network is regard as a n*n matrix where n stands for the number of forwarding devices in the network. Each (i,j) component of traffic matrix denotes the bandwidth of the flow from i-th node to j-th node. 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 this simulation, the traffic matrix is 500*500. The components of traffic matrix are generated from 10Mbps to 7Gbps randomly. About 20% links are overloaded when the Open Shortest Path First (OSPF) protocol is used in the network. This traffic matrix is used in following sections. In section 4.3, it is used as the background traffic which can't be scheduled. In section 4.4, it is re-routed based on load-balance. 4.3. End-to-End Path Optimization Based on the current state of the network, such as the traffic matrix in the network, network topology and network utilization, Quality of Service (QoS) and so on, the end-to-end path optimization is to find the best end-to-end path which is the lowest in metric value and each link of the path is far below link's threshold. The algorithm is a novel idea combining 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 finds the optimal paths for them. The selected paths bring the least congestion degree to the network. The simulation is tested with 1000 flows in 6 periods. The size of flows is from 10Mbps to 10Gbps. In each period, 100, 200, 100, 250, 150 and 200 flows are arrived respectively. The link utilization increment(UI) degree relative to the congestion threshold when the new flows are added into the network is shown in Fig.6. The first graph in Fig.6 is the UI with OSPF and the second graph is the UI with end-to-end path optimization. The average UI of graph one is more than 30%. After path optimization as shown in graph, the Expires January 17, 2018 [Page 8] Internet-Draft CCDR Scenario, Simulation and Suggestion July 18, 2017 average UI is less than 5%. In a conclude, the results show that the end-to-end path optimization has an eye-catching decreasing in UI degree relative to the path chosen based on OSPF. +-----------------------------------------------------------+ | * * * *| 60| * * * * * *| |* * ** * * * * * ** * * * * **| |* * ** * * ** *** ** * * ** * * * ** * * *** **| |* * * ** * ** ** *** *** ** **** ** *** **** ** *** **| 40|* * * ***** ** *** *** *** ** **** ** *** ***** ****** **| UI(%) |* * ******* ** *** *** ******* **** ** *** ***** *********| |*** ******* ** **** *********** *********** ***************| |******************* *********** *********** ***************| 20|******************* ***************************************| |******************* ***************************************| |***********************************************************| |***********************************************************| 0+-----------------------------------------------------------+ 0 100 200 300 400 500 600 700 800 900 1000 +-----------------------------------------------------------+ | | 60| | | | | | | | 40| | UI(%) | | | | | | 20| | | *| | * *| | * * * * * ** * *| 0+-----------------------------------------------------------+ 0 100 200 300 400 500 600 700 800 900 1000 Flow Number Fig.6 Simulation result with congestion elimination 4.4. Network temporal congestion elimination In general situation, there are often temporal congestion periods within part of the service provider's network. The network temporal congestion elimination is proposed which reroutes traffic from the congested paths to un-congested ones. The load-balance is achieved Expires January 17, 2018 [Page 9] Internet-Draft CCDR Scenario, Simulation and Suggestion July 18, 2017 after congestion elimination. And the cost of reroute traffic is also taken into consideration. Different degree of network congestion is simulated. About 20% links are congested with slightly or badly degree using the OSPF protocol. The congestion degree (CD) is defined as the link utilization beyond its threshold. For example, if the utilization of links is 90%, and its threshold is 80%, then its CD is 10%. The 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 2000 links exceed the threshold, and all the congestion degree is less than 3%. Thus, after schedule of the traffic in congestion paths, the degree of network congestion is greatly eliminated and the network utilization is indeed in balance. Before congestion elimination +-----------------------------------------------------------+ | * ** * ** ** *| 20| * * **** * ** ** *| |* * ** * ** ** **** * ***** *********| |* * * * * **** ****** * ** *** **********************| 15|* * * ** * ** **** ********* *****************************| |* * ****** ******* ********* *****************************| CD(%) |* ********* ******* ***************************************| 10|* ********* ***********************************************| |*********** ***********************************************| |***********************************************************| 5|***********************************************************| |***********************************************************| |***********************************************************| 0+-----------------------------------------------------------+ 0 0.5 1 1.5 2 After congestion elimination +-----------------------------------------------------------+ | | 20| | | | | | 15| | | | CD(%) | | 10| | | | | | Expires January 17, 2018 [Page 10] Internet-Draft CCDR Scenario, Simulation and Suggestion July 18, 2017 5 | | | | | * ** * * * ** * ** * | 0 +-----------------------------------------------------------+ 0 0.5 1 1.5 2 Link Number(*10000) Fig.7 Simulation result with congestion elimination 5. CCDR Deployment Consideration. With the above scenarios and simulation results, we can know it is necessary to find one general solution to cope with various complex situations and it is possible to accomplish the most complex optimal path computation function in centrally manner based on the underlay network topology and the real time traffic. [draft-wang-teas-native-ip] gives one basic solution for above scenario, such thought can be extended to cover requirements that are more concretes. 6. Security Considerations TBD 7. IANA Considerations TBD 8. Conclusions TBD 9. References 9.1. Normative References [RFC4655] Farrel, A., Vasseur, J.-P., and J. Ash, "A Path Computation Element (PCE)-Based Architecture", RFC 4655, August 2006,. [RFC5440]Vasseur, JP., Ed., and JL. Le Roux, Ed., "Path Computation Element (PCE) Communication Protocol (PCEP)", RFC 5440, March 2009, Expires January 17, 2018 [Page 11] Internet-Draft CCDR Scenario, Simulation and Suggestion July 18, 2017 . 9.2. Informative References [I-D.draft-ietf-teas-pce-control-function] A. Farrel, Q.Zhao et al. "An Architecture for use of PCE and PCEP in a Network with Central Control" https://datatracker.ietf.org/doc/draft-ietf-teas-pce-central- control/ September, 2016 [I-D. draft-ietf-teas-pcecc-use-cases] Quintin Zhao, Robin Li, Boris Khasanov et al. "The Use Cases for Using PCE as the Central Controller(PCECC) of LSPs https://tools.ietf.org/html/draft-ietf-teas-pcecc-use-cases-00 March,2017 [I-D. draft-wang-teas-pce-native-ip] A.Wang, Quintin Zhao, Boris Khasanov, Penghui Mi,Raghavendra Mallya, Shaofu Peng "PCE in Native IP Network" https://tools.ietf.org/html/draft-wang-teas-pce-native-ip-03 March 13, 2017 [I-D. draft-wang-pcep-extension for native IP] Aijun Wang, Boris Khasanov et al. "PCEP Extension for Native IP Network" https://datatracker.ietf.org/doc/draft-wang-pce-extension- native-ip/ 10. Contributors: Xiaoyan Wei Expires January 17, 2018 [Page 12] Internet-Draft CCDR Scenario, Simulation and Suggestion July 18, 2017 China Telecom Shanghai Company weixiaoyan@189.cn Qiong Sun sunqiong.bri@chinatelecom.cn Tingting Yuan Beijing University of Posts and Telecommunications yuantingting@bupt.edu.cn Dingyuan Hu Beijing University of Posts and Telecommunications hdy@bupt.edu.cn 11. Acknowledgments TBD Authors' Addresses Aijun Wang China Telecom Beiqijia Town, Changping District Beijing,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 Expires January 17, 2018 [Page 13] Internet-Draft CCDR Scenario, Simulation and Suggestion July 18, 2017 Caixia Kou Beijing University of Posts and Telecommunications No.10 Xitucheng Road, Haidian District Beijing,China koucx@lsec.cc.ac.cn Lu Huang China Mobile 32 Xuanwumen West Ave, Xicheng District Beijing 100053 China Email: hlisname@yahoo.com Penghui Mi Tencent Tencent Building, Kejizhongyi Avenue, Hi-techPark, Nanshan District,Shenzhen 518057, P.R.China Email kevinmi@tencent.com Expires January 17, 2018 [Page 14]