Multi-stage optimization framework for transporting 100-GbE over OTN with distributed differential delay compensation

The availability of novel communication services to telecom subscribers is creating a huge traffic growth over the underlying optical infrastructure. The expected high development costs of first generation 100 Gb/s equipment drives service providers to find alternative solutions for upgrading network capacity. Optical transport network (OTN) systems can use mature 10 Gb/s and 40 Gb/s equipment along with virtual concatenation (VCAT) to cost-effectively split and carry large data flows, such as the emerging 100 Gb/s Ethernet (100-GbE) signals. In addition, the combination of VCAT with multipath routing, in detriment of single-path forwarding, can improve load balancing, reducing the maximum capacity required per fiber link. However, the utilization of physical routes with distinct lengths introduces differential delay between the concatenated flows, which is typically compensated via buffering the flows in high-speed memories located at the destination node. These memories are very expensive, particularly when scaled to large sizes. Alternatively, distributed delay compensation architectures extend the compensation to the other path nodes, decreasing the individual size of memories. This paper proposes a multi-stage heuristic framework for optimizing the distributed compensation of inverse-multiplexed 100-GbE signals over OTN with the main objective of reducing the maximum buffer size per node while keeping capacity requirements to a minimum. The performance of the proposed framework, assuming execution time constraints, is compared to that of another heuristic method and an integer linear programming approach. The results obtained show that our framework reaches the optimal link load values, while outperforming both alternatives in reducing the buffer size.

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