1 / 28

Enhancing the Traffic Carrying Capacity of Optical Networks

Enhancing the Traffic Carrying Capacity of Optical Networks. Pramode K. Verma pverma@ou.edu Telecommunications Systems Program The University of Oklahoma – Tulsa. The Global Landscape. $1.2 trillion industry in 2002 Unsustainable rates of network deployment at the turn of the century

hollis
Télécharger la présentation

Enhancing the Traffic Carrying Capacity of Optical Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Enhancing the Traffic Carrying Capacity of Optical Networks Pramode K. Verma pverma@ou.edu Telecommunications Systems Program The University of Oklahoma – Tulsa June, 2004

  2. The Global Landscape • $1.2 trillion industry in 2002 • Unsustainable rates of network deployment at the turn of the century • $1.7 trillion loss in the market value of the industry • Selling phone service is not a sustainable business any more! June, 2004

  3. Outline • Traditional Telecommunication Systems • Optical Switching Technologies • Problems in Optical Networks with Wavelength Routing and Assignment • Proposed Solution June, 2004

  4. The Telecommunications Industry • A very unique industry • Driven by some very unique laws of nature • In robust health • Meltdown at the turn of the decade • Moderate (5-6%) growth anticipated in the future • Future Breakthroughs • Photonics • Wireless • Context sensitive applications June, 2004

  5. Common User Networks (1) June, 2004

  6. Common User Networks (2) June, 2004

  7. Common User Networks (3) • Characteristics • Probabilistic demands for service • “under provisioned” by design June, 2004

  8. Desired Response Carried Traffic Observed Response Incident Traffic Observed Characteristics of Telecommunication Networks (1) June, 2004

  9. Observed Characteristics of Telecommunication Networks (2) • Design Objectives • For a given topology maximize the network throughput or served traffic • Be fair among “classes” of traffic • Designer’s Tool Kit • Accept or reject traffic at source • Control routing flexibility June, 2004

  10. Telecommunication Networks (1) The North American hierarchical network (dashed lines show high-usage trunks). Note how the two highest ranks are connected in mesh. June, 2004

  11. Telecommunication Networks (2) • Legacy • Circuit Switched • Hierarchical • Evolving To • EOE • All Optical Lambda • Optical Burst Switching • Optical Packet Switching June, 2004

  12. Optical Switching Technologies Wavelength Routing And Assignment (RWA) Optical Burst Switching (OBS) Optical Packet Switching (OPS) June, 2004

  13. Wavelength Routing and Assignment (RWA) • Set up a light-path • Issues • Routing • Wavelength Assignment • Fairness • Throughput June, 2004

  14. Illustrative example NY WA MI NJ PA UT CA1 CO IL NE MD CA2 GA TX June, 2004

  15. Major Results (1) • Theorem 1: For any network topology, as the incident traffic intensity increases, the carried single-hop traffic between a source-destination node pair reaches a finite limit. June, 2004

  16. Major Results (2) • Theorem 2: For any network topology, as the incident traffic intensity increases, the carried multi-hop traffic (i.e., traffic with two or more hops) between any source-destination node-pair increases, but eventually goes to zero, after reaching a peak. June, 2004

  17. NY WA MI NJ PA UT CA1 CO IL NE MD CA2 GA TX June, 2004

  18. Illustrative Example: A Network with a Mesh Topology 3 2 4 1 6 5 June, 2004

  19. Routing and Traffic Table of the Mesh Topology June, 2004

  20. The Carried Traffic of the Mesh Topology June, 2004

  21. Impact of the Quantitative Understanding of the Network Behavior • Analytical results lead to quantification of the network performance • How do we use the new understanding to provide fairness while maximizing the network revenue June, 2004

  22. Higher Blocking Probability for Multi-hop Traffic SLA requires a maximum threshold for probability of blocking Implications of the Threshold? Fairness Problem June, 2004

  23. All available wavelengths shared by all traffic classes Reserved wavelengths for traffic between node si and dj Reserved wavelengths for traffic between node s1 and d1 … Shared wavelengths Reserved wavelengths for traffic between node sn and dn Incident traffic increases The Congestion Aware Wavelength Reservation Method (CAWR) June, 2004

  24. Blocking Probability with or without the CAWR Method June, 2004

  25. Carried Traffic with or without the CAWR Method June, 2004

  26. Network Revenue with or without the CAWR Method . We assume that for completed call connections, the service charge is $M/(Erlang*Hop). June, 2004

  27. Conclusion We have shown that as the incident traffic increases, the carried multi-hop traffic reaches a peak and then drops to zero, while the carried single-hop traffic goes to an asymptotic limit. When the incident traffic intensity of the network is arbitrarily high, the network can carry only single-hop traffic. We presented an algorithm called the Congestion Aware Wavelength Reservation to resolve the fairness problem in a DWDM network with multiple classes of traffic, while at the same time maximizing the throughput of the network and its attendant revenue. June, 2004

  28. Thanks & Question June, 2004

More Related