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Special issue on optical interconnect and integrated photonic chip technologies for hyper-scale computing|1 Article(s)
Virtualization-enabled dynamic functional split and resource mapping in optical data center networks [Invited]|On the Cover
Bo Tian, Shanting Hu, Qi Zhang, Xiaofei Huang, Lei Zhu, Huan Chang, Xiaolong Pan, and Xiangjun Xin
The heterogeneity of applications and their divergent resource requirements lead to uneven traffic distribution and imbalanced resource utilization across data center networks (DCNs). We propose a fine-grained baseband function reallocation scheme in heterogeneous optical switching-based DCNs. A deep reinforcement learning-based functional split and resource mapping approach (DRL-BFM) is proposed to maximize throughput in high-load server racks by implementing load balancing in DCNs. The results demonstrate that DRL-BFM improves the throughput by 20.8%, 22.8%, and 29.8% on average compared to existing algorithms under different computational capacities, bandwidth constraints, and latency conditions, respectively. The heterogeneity of applications and their divergent resource requirements lead to uneven traffic distribution and imbalanced resource utilization across data center networks (DCNs). We propose a fine-grained baseband function reallocation scheme in heterogeneous optical switching-based DCNs. A deep reinforcement learning-based functional split and resource mapping approach (DRL-BFM) is proposed to maximize throughput in high-load server racks by implementing load balancing in DCNs. The results demonstrate that DRL-BFM improves the throughput by 20.8%, 22.8%, and 29.8% on average compared to existing algorithms under different computational capacities, bandwidth constraints, and latency conditions, respectively.
Chinese Optics Letters
- Publication Date: May. 08, 2025
- Vol. 23, Issue 5, 050001 (2025)
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