Abstract

The growing popularity of high-speed mobile communications, cloud computing, and the Internet of Things (IoT) has reinforced the tidal traffic phenomenon, which induces spatio-temporal disequilibrium in the network traffic load. The main reason for tidal traffic is the large-scale population migration between business areas during the day and residential areas during the night. Traffic grooming provides an effective solution to aggregate multiple fine-grained IP traffic flows into the optical transport layer by flexibly provisioning lightpaths over the physical topology. In this paper, we introduce a comprehensive study on energy efficiency and network performance enhancement in the presence of tidal traffic. We propose and leverage the concept of stateful grooming to apply differentiated provisioning policies based on the state of network nodes. We formulate and solve the node-state-decision optimization problem, which can decide the specific state of network nodes when a certain traffic profile is given, considering the trade-off between energy efficiency and blocking performance with a multi-objective integer linear program (MOILP). Then, we propose an online traffic-aware intelligent differentiated allocation of lightpaths (TIDAL) algorithm, based on stateful grooming and the MOILP, to accommodate the dynamic tidal traffic. Our illustrative numerical results show that the proposed method can achieve a significant performance improvement in an energy-efficient way.

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