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Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 39,
  • Issue 10,
  • pp. 3011-3024
  • (2021)

Auxiliary-Graph-Based Energy-Efficient Traffic Grooming in IP-Over-Fixed/Flex-Grid Optical Networks

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Abstract

Due to the development of broadband access technologies including FTTx and 5G, the traffic in metro and core networks is forecasted to be more dynamic. To support this dynamicity, flex-grid elastic optical networks (EONs) have started to become prolific over the past few years. During the migration from the legacy fixed-grid wavelength division multiplexing optical networks to flex-grid EONs, a transition technology called the fixed/flex-grid optical network has become popular. In such fixed/flex-grid networks, the energy consumption caused by serious capacity mismatch between variable IP traffic and the different optical channel capacities is significantly high to be ignored. In fact, energy-efficient traffic grooming (i.e., to aggregate multiple fine-grained IP flows and map them onto a lightpath) is a challenge in IP-over-fixed/flex-grid optical networks because co-existing fixed-grid and flex-grid nodes have different traffic grooming ability and energy consumption models. To overcome the challenge, we propose an auxiliary-graph-based energy-efficient traffic-grooming (EETG) algorithm in IP-over-fixed/flex-grid optical networks for the first time. The construction of an auxiliary graph (AG) model for each connection request is one of the core steps. The well-designed weight-assignment scheme of the AG establishes the relationships between traffic grooming operations and specific energy consumption models. The final traffic grooming operations are undertaken based on the calculated weight-minimized path. The simulation results show that the EETG algorithm achieves 1) the least energy consumption compared with the state-of-the-art traffic grooming algorithms under the non-blocking scenario; and 2) achieves the tradeoff between energy consumption and blocking probability under the blocking scenario.

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