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ONOS-Based VIM Implementation


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Patrick Liu, Huawei; XiongYan Tang, china Unicom; Brian O'Connor, ON.LAB

Published in: Software
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ONOS-Based VIM Implementation

  1. 1. ONOS-based VTN implementation XiongYan Tang China Unicom Patrick Liu Huawei Technologies Inc Brian O’Connor ON.LAB
  2. 2. 2 Agenda Requirements (XiongYan Tang) Architecture Overview ONOS (Brian O’Connor) VTN (Patrick Liu) Demo (Patrick Liu) Scalability HA VM Migration
  3. 3. 3 China Unicom New Generation Network Architecture: CUBE-Net 2.0 Application ComponentApplication layer API Data-oriented Network (DoN) Cloud Interconnection Customer-oriented Network (CoN) NaaS …… NaaS API Service Collaboration and Orchestration Application Component Application Component Basic NE Southbound Control East-West Integration Northbound Openness East-West Integration Internet-oriented Network (IoN) IP + Optical network bearing plane ① Cloud Service Access① Ubiquitous-Broadband Access ③ Ultra-Broadband Elastic Pipe Base DC Base DC Base DC Base DC Regional DC Regional DC MAN aggregation Mobile backhaul Edge DC Fixed broadband Ubiquitous Access Wireless broadband Mobile broadband ④ Cloud-enabled Network Service Platform Virtual Network Resource Management Network Control Cloud Service
  4. 4. 4 CUBE-Net: Cloud and Network Collaboration E2E Network and Cloud Orchestration (ICT Orchestration) SDN Orchestrator NFV Orchestrator Cloud/DC Orchestrator Legacy network Orchestrator SDN Controller VNFM VIM(NFV&DC) EMSCloud VM Switch/vSwitch Router/vRouter Service route Access (SDN) Service route WAN (SDN) IP Core (SDN) VM API API Application ComponentApplication layer Application Component Application Component Northbound interface for capability opening Deployment collaboration Management collaboration Service collaboration Service chain Service chain Edge Cloud (NFV) Regional Cloud (NFV & Cloud) Base Cloud + Third-party Cloud
  5. 5. 5 CUBE-Net: On-demand NFV Services based on Cloud vCPE, vBNG, vEPC, vCDN vIMS, Video, vVAS, APP vBBU, vOLT VNFM, VIM, EMS IP device Backbone IP device IP device Base DC Optical transmission Metro Regional DC Compute Network Storage CPE MxU ONT RRU OLT User-oriented VNF Control-oriented VNF Application-oriented VNF Edge DC Management cloud Function cloud Service cloud Control cloud vSwitch, vRouter ICT Service Orchestrator OSS, BSS, Big Data CPE, IPRAN/ME, TSDN controller IP + Optical, DCI, DC controller 1. Flattened: ultra-broadband access, one-hop reach 3. Intensive: service provisioning and orchestration2. Decoupling: control and management Optical transmission Optical transmission Optical transmission IP device Compute Network Storage Compute Network Storage
  6. 6. 6 Our view on NFV VIM NFV VIM Scalability Open AvailabilityAutomatic
  7. 7. 7 ONOS Distributed Architecture NB Core API Distributed Core (state management, notifications, high-availability & scale-out) SB Core API Protocols Providers Protocols Providers Protocols Providers Protocols Providers AppsApps
  8. 8. 8 ONOS Distributed Architecture NB Core API Distributed Core (state management, notifications, high-availability & scale-out) SB Core API Protocols Providers Protocols Providers Protocols Providers Protocols Providers AppsApps Distributed Core (state management, notifications, high-availability & scale-out) SB Core API NB Core API Providers Providers Providers Providers Protocols Protocols Protocols Protocols
  9. 9. 9 Architectural Tenets • High-availability, scalability and performance • required to sustain demands of service provider & enterprise networks • Strong abstractions and simplicity • required for development of apps and solutions • Protocol and device behavior independence • avoid contouring and deformation due to protocol specifics • Separation of concerns and modularity • allow tailoring and customization without speciating the code-base
  10. 10. 10 ONOS Flow and Intent Throughput Linear Scale out Characteristics i Linear Scale out Characteristics in North bound Source: ONOS white paper on performance High performance  As demands on the SDN control plane grow, either due to an increase in the size of the network or due to an increase in the number of network control applications, ONOS can scale by adding additional instances to the cluster. (linear scale-out characteristics in both the southbound and northbound)
  11. 11. 11 ONOS Topology (Switch, Port) Event Latency 50 and 60 ms 1 and 3 ms 5 and 7 ms 3 and 4 ms
  12. 12. 12 ONOS based VTN Architecture OVS Service VM (FW) VM Compute Node OVS VMVM Compute Node OVS VMVM Compute Node Neutron ML2 Plugin L3 Plugin Nova OVSDB OF1.3 SFC Manager Neutron API SFC Plugin VTN Manager Distributed VTN store VTN Overlay Net Topology Device (OVS) Host (VM) Link (VxLAN) Flow Rule Tunnel Packet Stats Master OVS DHCP Network Node DHCP VxLAN VxLAN Tunnel Port Ingress SF Port CORE Provider Egress SF Port Single Bridge br-int in Network and Compute node OF based L3 Forwarding (No DVR) Ex Traffic is forwarded and received directly by compute node. ARP proxy on each compute node Physical and Overlay Network Flow Rule management Full Mesh Overlay network with two variations: 1. create two tunnel-ports per VxLAN; 2. Create only one tunnel-ports per OVS, which shared by all of the VxLANs VTN is an Application Distributed VTN Stores Multiple bundles Mastership Port External Port 1 2 Classifier ARP DNAT L3 FWD SNAT L2 FWD Data path pipeline3
  13. 13. 13 Demo 1: VTN Management and Scalability Swift Neutron Plugins Nova OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS OVS Server Server Server Full Mesh Container OVS VTN Tunnel FlowR OVSDB OF1.3 Topo
  14. 14. 14 Demo 2: High Availability Swift Neutron Plugins Nova OVS 1 VMVM OVS 2 VMVM OVS 3 VMVM Node 1 Node 2 Node 3 Master Standby
  15. 15. 15 Demo 3: Host Live Migration OVSOVS VM2VM3 VM4VM1 Neutron Plugins Nova VM1 Topology Host 1 Host 1
  16. 16. Copyright©2015 Huawei Technologies Co., Ltd. All Rights Reserved. The information in this document may contain predictive statements including, without limitation, statements regarding the future financial and operating results, future product portfolio, new technology, etc. There are a number of factors that could cause actual results and developments to differ materially from those expressed or implied in the predictive statements. Therefore, such information is provided for reference purpose only and constitutes neither an offer nor an acceptance. Huawei may change the information at any time without notice.