2. Robust Designs for WDM Routing and Provisioning Jeff Kennington & Eli Olinick Southern Methodist University Augustyn Ortynski & Gheorghe Spiride Nortel Networks

3. Equipment modeling – sample network link LTE …… …… TE …… LTE …… …… TE ……

4. Unmet demand Satisfied demand Excess capacity Underprovisioned Case DallasAtlanta Perfect Match Case LAPhoenix Overprovisioned Case BostonNYC

5. Overprovisioned Case Underprovisioned Case Perfect Match Case UnderprovisioningOverprovisioning Regret

6. Overprovisioned Case Underprovisioned Case Perfect Match Case UnderprovisioningOverprovisioning Regret

7. If the point-to-point demands are known, then we can develop a perfect design. If the demands (which are forecasts) are not known with certainty, then we develop a design that attempts to minimize regret over a range of possible demands.

8. 7 4 3 1 2 5 6 Atlanta San Francisco Los Angeles Dallas Chicago Boston New York Example

9. ATLBOSCHIDALLANYSF ATL-170110941289345413463952 BOS-480283647483384947 CHI-1491323012623415 DAL-2182 2774 LA-4413612 NY-4652 SF- Distance Matrix (KM)

10. ATLBOSCHIDALLANYSF ATL-500370880300950- BOS--860710-740 CHI----- DAL---- LA--- NY-540 SF- Scenario #1 Demand Matrix (DS3s)

11. ATLBOSCHIDALLANYSF ATL-15001370188013001950- BOS--18601710-1740 CHI----- DAL---- LA--- NY-1540 SF- Scenario #2 Demand Matrix (DS3s)

12. ATLBOSCHIDALLANYSF ATL-25002370288023002950- BOS--28602710-2740 CHI----- DAL---- LA--- NY-2540 SF- Scenario #3 Demand Matrix (DS3s)

13. 7 4 3 1 2 5 6 Atlanta San Francisco Los Angeles Dallas Chicago Boston New York Scenario #1 Solution

14. 7 4 3 1 2 5 6 Atlanta San Francisco Los Angeles Dallas Chicago Boston New York Scenario #2 Optimal Solution

15. 7 4 3 1 2 5 6 Atlanta San Francisco Los Angeles Dallas Chicago Boston New York Scenario #3 Solution

16. 7 4 3 1 2 5 6 Atlanta San Francisco Los Angeles Dallas Chicago Boston New York Robust Solution

17. The End