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Node - Inclusive Span Survivability in an Optical Mesh Transport Network John Doucette and Wayne D. Grover TRLabs and University of Alberta Edmonton, AB, Canada john.doucette@trlabs.ca, grover@trlabs.ca NFOEC 200 3 Orlando, FL , USA 7 - 11 September 200 3. Introduction. Span Restoration
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Node-InclusiveSpanSurvivability in an Optical Mesh Transport Network John Doucette and Wayne D. Grover TRLabs and University of Alberta Edmonton, AB, Canada john.doucette@trlabs.ca, grover@trlabs.ca NFOEC 2003 Orlando, FL, USA 7-11 September 2003
Introduction • Span Restoration • Localized and shorter restoration paths • Faster and easier control of transmission effects • Less capacity efficient • No ability to recover from node failures • End-to-End Path Restoration • More capacity efficient • Inherent ability to recover from node failures • Operationally more complicated • Many nodes involved, and restoration paths are lengthy • Greater average delay • Can we modify span restoration to protect node failures? • Will this combine benefits of span and path restoration?
Span Restoration Path Restoration B B custodial nodes X X custodial node X C X C custodial node A Z A Z Y Y D D Node-Inclusive Span Survivability NA NZ custodial regions B X X C A Z Y node-inclusive span entity D Node-Inclusive Span Survivability Concept
X X A A B B C C D D E E A B C D E Node Failure Recovery: X NISS Operational Details Span Failure Recovery:
restoration route custodial node B Y D custodial node A Z O X X X C X custodial node D custodial regions custodial node O restoration route NISS Operational Details(2)
Integer Linear Programming Model Objective Function: • Minimize cost of spare capacity Subject To: • Restoration flow for all span failure scenarios • Spare capacity allocation for span failures • including stub release • Restoration flow for all node failure scenarios • Spare capacity allocation for node failures • including stub release
Computational Aspects • Test networks • Group A: Nine small test networks (9-node 17-span to 11-node 26-span) • Group B: Three families of networks of varying average nodal degree (15-node to 25-node) • Traffic demands • Group A: Various, as per networks’ sources • Group B: Uniform random demands from 1 to 10 wavelengths • Working capacity is shortest path routed • Eligible route enumeration • At least five eligible restoration routes per failure scenario • ILP solution method • Implemented in AMPL and solved using CPLEX 7.1 MIP • 4-processor UltraSparc Sun Server, 450 MHz, 4 GB RAM • Solved to within 0.01% of optimality • Most problems solved in several seconds or minutes
Results Test Networks: Group A
Results (2) Test Networks: Group B 15-node family
Results (3) Test Networks: Group B 20-node family
Results (4) Test Networks: Group B 25-node family
Concluding Remarks • Node failure protection is inherent • and we can explicitly guarantee it • Spare capacity requirements are good • significantly below span restoration • approaching path restoration (within 0% to 10%) • Easily amenable to dynamic service provisioning • working capacity envelope can apply • Localized restoration paths make operational aspects much easier than path restoration