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The Research of Applying Random Early Blocking strategy to Dynamic Lightpath Routing

This research explores applying Random Early Blocking strategy to Dynamic Lightpath Routing for efficient resource utilization and reduced blocking probability. The study compares SCP, WSCP, and EWSCP strategies and includes simulation results to demonstrate the effectiveness of the proposed approach.

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The Research of Applying Random Early Blocking strategy to Dynamic Lightpath Routing

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  1. The Research of Applying Random Early Blocking strategy to Dynamic Lightpath Routing National Yunlin University of Science & Technology

  2. Outline • Background • Related works • SCP, WSCP, EWSCP • Layered-Graph model • Simulation of routing strategies • Random Early Blocking (REB) • Simulation results • Conclusion

  3. Background • Communication service • More bandwidth is needed by customs • The poplar services • Internet, cell-phone……

  4. Background • WDM (Wavelength Division Multiplex) • Wavelengths are carried on a fiber • Bandwidth grows much

  5. Background • WDM network routing strategies • Fixed routing • Alternative routing • Adaptive routing • Routing & Wavelength Assignment (RWA) • Wavelength continuous constrain • Wavelength conversion • Converter placement

  6. The adaptive routing strategies • To search lightpath as calls coming in • Routing information • Distance vector (RIP) • Link state (OSPF)

  7. Adaptive routing – Related works • Shortest Cost Path (SCP) • The path cost function • Equal-weighted link cost • Disadvantage • Some links may be heavy traffic load • Higher blocking probability

  8. Adaptive routing – Related works • Weighted Shortest Cost Path (WSCP) • Distributing traffic load • Better network utilization • Lower blocking probability • The path cost function • Liner link cost function assignment

  9. Adaptive routing – Related works • Exponential Weighted Shortest Cost Path (EWSCP) • Light load shortest path • Medium load load balance • Heavy load avoid exhaust all wavelength on a link • Link cost function

  10. Layered-graph model • Physical network topology • N(R,L,W) • R is the set of routing nodes • L is the set of links • W is the set of wavelengths per link

  11. Layered-graph model – logical network

  12. Layered-graph model – logical network • N’(V,E,X) • V is the set of routing nodes • E is the set of links • X is the set of wavelengths per link • R’ is the set of routing nodes with conversion • Number of V is : • Number of E

  13. Simulation parameters • W=32 per network link • Full converter, sparse converter, non-converter • Different network topologies • Network traffic : • Link congestion index :

  14. Network topology 14-nodes NSFNET 8-nodes Ring

  15. Network topology 14-nodes Random Net

  16. Ring Sparse converter Full converter

  17. NSFNET full-converter

  18. NSFNET Sparse converter Non-converter

  19. Random Full converter Full converter

  20. EWSCP results • Reducing blocking probability • Load balance • Better performance than WSCP and SCP Rand Sparse converter

  21. Random Early Blocking (REB) • Early (set active threshold) • Before resource assign out • Resource conservation as heavy load • Random Blocking • Block long-lightpath randomly • Random function • Result • Reduce blocking probability much as heavy load

  22. NSFNET Left-top: Non-converter Left-bottom: Sparse converter Right: Full-converter

  23. NSFNET (full converter)

  24. Random Sparse converter Full converter

  25. Random (full converter)

  26. Conclusion • We proposed EWSCP algorithm to balance traffic load • EWSCP enhance performance than WSCP • Use exponential link cost function • Applied REB strategy to conserve resource • Increase probability of success for shorter lightpath • As heavy load, algorithm with REB has excellent performance

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