VT Reconfiguration

1. VT Reconfiguration • Traffic is dynamic: Traffic intensities change in time. VT may be inefficient for new traffic. • Problem: How can we change the VT to accommodate the new traffic intensities? • Solutions: • Redesign the VT. • Change some lightpaths  Reconfiguration. Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

2. 0 1 0 1 3 2 3 2 Illustrative Example 0 1 0 1 2 3 0 0 1 0 0 1 0 0 1 0 2 0 0 0 1 3 1 0 0 0 3 2 0 1 2 3 0 0 0 0 1 1 1 0 0 0 2 0 1 0 0 3 0 0 1 0 Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

3. Motivation • Backbone network • Slow changes in traffic Change the virtual topology slowly. t1 t2 Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

4. Earlier Approaches • Wait until VT becomes inefficient. • Run an optimization algorithm  new VT. • Run a transformation algorithm.Old VT New VT • Branch-exchange method Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

5. Our Approach • Observe the traffic Adapt VT • New VT adjacent to old VT: Only 1 lightpath is different. • Simple reconfiguration. • Simple transition. continuously. Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

6. Optimization Goals • Using minimum number of lightpaths. • Load balancing. • Minimizing the number of changes: transition period’s length traffic rerouting Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

7. Main Idea • Add or delete 1 lightpath at a time. • Add a lightpath if some lightpaths are heavily loaded. • Delete a lightpath if some lightpaths are lightly loaded. • 2 parameters: • High watermark • Low watermark Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

8. Implementation • Traffic loads on links are observed periodically:Observation period T. • T should be small enough to follow the changes. • Typically few 100s Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

9. Adaptation Algorithm Start with initial topology. Every T seconds do: Compare the load Li on each lightpath i with the watermarks. ifLi > WHthen add an appropriate lightpath. else ifLi < WLthen delete an appropriate lightpath. else do not adapt the VT. Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

10. MILP • Objective: Minimize Lmax • Constraints: (1) Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

11. MILP (cont.) • Constraints: if Lmax > WH then if Lmin < WL then (2) Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

12. Comparison • We compare MILP to a full-reconfiguration method. Start with initial topology. Every T’ seconds do: Find the minimum #lightpaths for the new traffic pattern. Find the virtual topology such that: It has minimum #lightpaths. It requires minimum #changes from the previous topology. Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

13. Results (MILP) N = 6 W = 4 Tx = 4 WH = 0.8 Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

14. Results (MILP) Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

15. Results (Heuristic) Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

16. Results (Heuristic) Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)

17. Results (Heuristic) Virtual Topology Adaptation in WDM Mesh Networks (for ECS 259: A. Gencata and B. Mukherjee, UC Davis)