Lecture5c

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Lecture5c

  1. 1. Routing and Wavelength Assignment for Wavelength-Routed WDM Networks Combined routing and wavelength assignment problem Routing x static: ILP formulation x dynamic: on-line algorithms Wavelength assignment x static: graph coloring approach x dynamic: heuristics A new wavelength assignment heuristic ECS 259 -- H. Zang and B. Mukherjee, UC Davis 1
  2. 2. RWA Problem statement Wavelength-continuity constraint ECS 259 -- H. Zang and B. Mukherjee, UC Davis 2
  3. 3. Combined Routing and Wavelength Assignment Problem ECS 259 -- H. Zang and B. Mukherjee, UC Davis 3
  4. 4. Routing - ILP Formulation ECS 259 -- H. Zang and B. Mukherjee, UC Davis 4
  5. 5. Routing - Algorithms For Dynamic Traffic Fixed routing (On/Off line) Fixed-alternate routing (On/Off line) Adaptive routing (On line) x adaptive shortest path routing x least congested path routing ECS 259 -- H. Zang and B. Mukherjee, UC Davis 5
  6. 6. Wavelength Assignment with Known Lightpaths and Routes - Graph Coloring Construct an auxiliary graph G(V,E) Color the nodes of the graph G such that no two adjacent nodes have the same color Sequential graph coloring approaches ECS 259 -- H. Zang and B. Mukherjee, UC Davis 6
  7. 7. Wavelength Assignment Heuristics Random Least Loaded First-Fit MAX-SUM Least-Used/SPREAD Relative Capacity Loss Most-Used/PACK Wavelength Reservation Min-Product Protecting Threshold ECS 259 -- H. Zang and B. Mukherjee, UC Davis 7
  8. 8. Illustrative Example wavelengths P1:(2,4) λ3 λ2 λ1 λ0 0 1 2 3 4 5 6 Note: control network not shown. All wavelengths shown are for data traffic ECS 259 -- H. Zang and B. Mukherjee, UC Davis 8
  9. 9. Calculation of Max-Sum wavelengths P1:(2,4) λ3 λ2 λ1 WPC: λ0 Wavelength-path 0 1 2 3 4 5 6 Capacity wavelengths WPC loss of each path on each λ Total WPC loss P2:(1,5) P3:(3,6) P4:(0,3) λ3 1 0 0 1 Wavelength λ2 1 1 0 2 selected: λ1 0 1 0 1 λ0, λ1, or λ3 λ0 0 0 1 1 ECS 259 -- H. Zang and B. Mukherjee, UC Davis 9
  10. 10. Calculation of Relative Capacity Loss wavelengths P1:(2,4) λ3 λ2 λ1 Wavelength selected: λ0 λ1 or λ3 0 1 2 3 4 5 6 wavelengths RCL of each path on each λ Total RCL P2:(1,5) P3:(3,6) P4:(0,3) λ3 0.5 0 0 0.5 λ2 0.5 0.5 0 1 λ1 0 0.5 0 0.5 λ0 0 0 1 1 ECS 259 -- H. Zang and B. Mukherjee, UC Davis 10
  11. 11. Simulation Network 2 1 2 1 1 0 1 1 3 1 1 5 4 2 Connection management protocol: link-state ECS 259 -- H. Zang and B. Mukherjee, UC Davis 11
  12. 12. Results from Others’ Publication Source: S. Subramaniam and R. A. Barry, “Wavelength assignment in fixed routing WDM networks,” Proc. ICC'97 - International Conference on Communications, Montreal, Canada, vol. 1, pp. 406-410, June 1997. 5x5 20-node bidirectional unidirectional R mesh-torus, ring, load/W R FF, MU load/W = 1 Erlang = 25 Erlangs FF MS WC WC MU, MS # of wavelengths # of wavelengths (a) (b) ECS 259 -- H. Zang and B. Mukherjee, UC Davis 12
  13. 13. Computational Complexity Wavelength reservation & Protecting threshold - constant Random & First-Fit - O(W) Min-Product & Least-Loaded - O(NW) Least-Used & Most-Used - O(LW) Max-Sum & Relative Capacity Loss - O(WN3) where W - # of wavelengths, N - # of nodes, L - # of links ECS 259 -- H. Zang and B. Mukherjee, UC Davis 13
  14. 14. Distributed RCL Algorithm P1:(2,4) λ3 λ2 λ1 λ0 0 1 2 3 4 5 6 Wavelength 0 1 2 3 4 5 6 Subtotal Wavelength λ3 RCL table at Node 2 0 1/3 0 1/4 1/4 1/3 0 11/12 * selected: λ3 λ2 0 1/3 0 1/4 1/4 1/3 1/2 17/12 λ1 0 0 0 1/4 1/4 1/3 1/2 13/12 λ0 1 1/3 0 1/4 1/4 0 0 19/12 ECS 259 -- H. Zang and B. Mukherjee, UC Davis 14
  15. 15. Characteristics of Distributed RCL Less state information is exchanged Faster computation of wavelength assignment upon a connection request Can be combined with adaptive routing ECS 259 -- H. Zang and B. Mukherjee, UC Davis 15
  16. 16. Simulation Network 2 1 2 1 1 0 1 1 3 1 1 5 4 2 Average propagation delay between two nodes: 0.107 ms Average hop distance: 1.53 ECS 259 -- H. Zang and B. Mukherjee, UC Davis 16
  17. 17. Simulation Results of Distributed RCL Comparison of DRCL with adaptive routing and RCL with fixed routing ECS 259 -- H. Zang and B. Mukherjee, UC Davis 17
  18. 18. Conclusion for RWA Heuristics Complexity Performance Least Used O(LW) Ordered in Random O(W) increasing order Min-Product O(NW) First-Fit O(W) Most-Used O(NW) Least-Loaded O(LW) Max-Sum O(WN3) Relative Capacity Loss O(WN3) L: # of links, N: # of nodes, W: # of wavelengths ECS 259 -- H. Zang and B. Mukherjee, UC Davis 18
  19. 19. Future Research Survivable wavelength-routed WDM networks x previous work: static traffic & single link failure [S. Ramamurthy 1998] x higher layer protection -logical topology design with bundle cut in mind x WDM layer protection - dynamic traffic ECS 259 -- H. Zang and B. Mukherjee, UC Davis 19
  20. 20. Future Research (Cont’d) Managing multicast connections in wavelength-routed WDM networks x KMB x Bellman-Ford x Chain ECS 259 -- H. Zang and B. Mukherjee, UC Davis 20

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