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With the widespread application of edge computing technology in 5G networks, edge computing has become an important component of the 5G core network. This paper focuses on how to optimize the central control functions of the 5G core network (5GC) in the edge computing environment, particularly the design and implementation of the Session Management Function (SMF) to address the challenges posed by the distributed edge computing environment. Two optimization design schemes are proposed: the I-SMF and L-SMF schemes. The I-SMF scheme introduces I-SMF to offload edge computing traffic and policy processing tasks, thereby reducing the burden on the central SMF. The L-SMF scheme, on the other hand, fully delegates the management of edge computing traffic to the local SMF, further alleviating the pressure on the central SMF while enhancing the flexibility and efficiency of local edge computing. By comparing the advantages and disadvantages of the two schemes, this paper analyzes their differences in tunnel setup, policy updates, and implementation complexity. Ultimately, the proposed optimization design improves the performance of 5GC in the edge computing environment, reduces the pressure on central control functions, and ensures the efficiency and stability of edge computing.

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Optimization Design of SMF in 5G Core Network Under Edge Computing Environment

  • 会议论文

  • 发表日期：

    2026年

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  • Chenglong Zhang,
  • Yupeng Chen,
  • Min Zhao,
  • Hao Su,
  • Lina Cui

摘要

With the widespread application of edge computing technology in 5G networks, edge computing has become an important component of the 5G core network. This paper focuses on how to optimize the central control functions of the 5G core network (5GC) in the edge computing environment, particularly the design and implementation of the Session Management Function (SMF) to address the challenges posed by the distributed edge computing environment. Two optimization design schemes are proposed: the I-SMF and L-SMF schemes. The I-SMF scheme introduces I-SMF to offload edge computing traffic and policy processing tasks, thereby reducing the burden on the central SMF. The L-SMF scheme, on the other hand, fully delegates the management of edge computing traffic to the local SMF, further alleviating the pressure on the central SMF while enhancing the flexibility and efficiency of local edge computing. By comparing the advantages and disadvantages of the two schemes, this paper analyzes their differences in tunnel setup, policy updates, and implementation complexity. Ultimately, the proposed optimization design improves the performance of 5GC in the edge computing environment, reduces the pressure on central control functions, and ensures the efficiency and stability of edge computing.