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Zdravko Bozakov

Towards Virtual Routers as a Service 6th GI/ITG KuVS Workshop on “Future Internet ” November 22, 2010 Hannover. Zdravko Bozakov. Towards Virtual Routers as a Service. Talk o utline Virtualization overview Use case: virtual routers as a service Problem statement

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Zdravko Bozakov

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  1. Towards Virtual Routers as a Service 6th GI/ITG KuVS Workshop on “Future Internet”November 22, 2010Hannover Zdravko Bozakov

  2. Towards Virtual Routers as a Service • Talk outline • Virtualization overview • Use case: virtual routers as a service • Problem statement • Resource allocation algorithm • Virtual router location selection • In brief • Virtual router architecture • Live-migration • Summary and outlook

  3. Network Virtualization Overview • Virtualization aims to decouple logical and physical network resources and increase network flexibility • Variable mapping of physical and logical entities • Slice network hardware for multiple customers • Handle multiple network devices using a single control plane • Live-migration of logical routers • Load balancing (capacity, routing tables, CPU) • Scheduled router maintenance • Energy conservation

  4. Virtual Routers as a Service

  5. Virtual Routers as a Service • On-demand provision of connectivity over core network • Enterprise branch offices • Regional providers • University campuses • Single virtual router for edge interconnection • Reduction of customer management overhead • Consolidation of provider resources and transparent remapping • Port relay nodes (PRN) • Forward traffic to virtual router (root node)

  6. Problem Statement What we have: • Backbone network • Weighted graph Gwith weights W • Link utilization U and capacityC (u/c) • Customer requirements • Subset of edge nodes Γ • Capacity demand Dfor edge nodes γ What we need: • Optimal location of VR root node R • Optimal paths from R to Γ satisfying capacity constraints R W=1

  7. Path Selection Algorithm Trivial case: unlimited backbone capacity • For each γ calculate shortest path to R(e.g. Dijkstra) • Does not work for capacity constrained networks • Solution with constraints: flow network theory (successive shortest paths) w=0C=1 w=0 C=4 DST SRC

  8. Root Node Selection • Optimal location of root node R • Minimize the cost S of bandwidth consumed by the VR links V • Root selection using total enumeration • Nodes with insufficient resources are pruned (e.g. capacity, CPU, memory) • Example: optimal root node locations with total cost S=4

  9. Virtual Router Architecture • Root node: hardware accelerated virtual router • Control plane virtualization using standard VMson commodity servers • Programmable data plane using Openflow-enabled switches • Port relay nodes (PRN) • Forward packets based on L2 virtual router addresses along computed paths • Openflow implementation

  10. Live Router Migration • Virtual router architecture allows live router migration • Setup outbound PRN paths for new root node R* • Clone forwarding table from old root R and remap physical ports • Control plane continuously updates routing tables on R and R* • Asynchronously setup inbound paths for R* • Tear down old paths and root node Watch the demo during the break!

  11. Conclusion and Outlook • Conclusion • On-demand connectivity usingsingle logical router instance reduces management overhead • Presented approach allows optimal computation of paths to a router located within network core • Basic root node selection strategy • Architecture is capable of live-migration • Outlook • Refine path selection algorithm and analyze alternative approaches • Optimize root node selection method • Detailed evaluation of live-migration performance • Implement and evaluate fallback strategies

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