An Enhanced Framework for 5G Network Slicing Optimization With Prioritized Resource Allocation Using 2-Edge-Connected Subgraphs

Emerging 5G network slicing technologies require robust optimization frameworks to ensure efficient resource allocation and path protection. This paper presents an improved slicing optimization model that enhances resource distribution while maintaining computational efficiency. The model builds upon our previously developed framework, which utilizes 2-edge-connected subgraphs for path protection. The proposed enhancement introduces prioritized resource allocation by integrating a weighting factor that optimally balances slice importance and resource distribution, without increasing algorithmic complexity. The model is evaluated against our previous 2-edge-connected subgraph framework. Simulation results demonstrate that the improved model achieves better resource efficiency and fairness, while maintaining network resilience and ensuring optimal performance in dynamic network environments. The proposed framework provides valuable insights for network operators in optimizing 5G slicing strategies under constrained resource conditions.