Software-Defined Data Center Networks (SDDCN) represent a transformative approach to data centre architecture, integrating Software-Defined Networking (SDN) principles to efficiently manage and optimize network resources. With the rapid proliferation of Internet technologies, IoT, smart devices, and fog & edge computing, data centre traffic has surged over the past decade and is expected to grow exponentially. Given the dynamic and unpredictable nature of data centre workloads and traffic patterns, Traffic Engineering (TE) is crucial in optimizing resource utilization and enhancing overall network performance.

Survey reports highlight an increasing demand for data centre services, driving unprecedented global expansion. However, data centres are among the most energy-intensive IT infrastructures, with energy consumption projected to surpass other sectors. As a result, energy optimization must be a primary TE objective, ensuring reduced power consumption without compromising performance.

TE in SDDCN is an NP-hard continuous optimization problem, making designing an energy-efficient traffic engineering algorithm particularly challenging. This study explores key challenges in this domain and emphasizes the need for innovative TE mechanisms prioritising energy efficiency and network performance.