Resource Allocation for Ultra-Low Latency Virtual Network Services in Hierarchical 5G Network

To support ultra-low latency 5G services flexibly and use limited resources in Multi-access Edge Computing (MEC) servers efficiently, the study of latency-aware optimal hierarchical resource allocation for Service Function Chains in 5G becomes essential. In this regard, we address this resource allocation problem, for the first time, by designing a Mixed Integer Linear Programming (MILP) model based on a hierarchical 5G network interconnecting multiple MEC nodes. The objective is to minimize the total latency from five sources: processing, queueing, transmission, propagation, and optical-electronic-optical conversion. Experimental results prove that ultra-low latency requirements can be guaranteed and maximum usage of MEC node resources can be obtained. Then, a data rate-based heuristic algorithm is proposed, which can get ≤1.5 approximation ratio under different workload scenarios and achieve at least 1.7 times as much service acceptance ratio as the baseline approach.