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Dynamic programming-based reconfiguration algorithm for optimized 5GC refactoring
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AI
DOI：10.1016/j.future.2025.108214.png)
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Abstract
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• We utilize the previous design of the quantitative indicators to evaluate the queuing delay and resource allocation cost. As a result, we can evaluate the performance in a more time-efficient manner. • We transform and reconstruct the previous optimization problem formulation with the two quantitative indicators, MER and MUD, as the objective function instead of the queuing delay and resource allocation cost. • This article proposes a dynamic programming-based heuristic algorithm to derive a near-optimal 5G core network configuration (DPR-5GC) to shorten the execution time of the real-time dynamic reconfiguration. • The execution time of the heuristic algorithm for the DPR-5GC is about 0.026s, while the execution time of the GUROBI Optimizer for the optimization problem is about 5896 min; that is, the DP-based reconfiguration algorithm performs approximately thirteen million times faster than the GUROBI Optimizer.
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