Dynamic network slicing for resource allocation in 5G/B5G networks: An optimization-based approach

The rapid proliferation of heterogeneous services, such as Ultra-Reliable Low-Latency Communication (URLLC), enhanced mobile broadband (eMBB), and Massive Machine Type Communications (mMTC), requires 5G/B5G networks to support dynamic and scalable resource allocation frameworks. This paper presents a Context-Aware Resource Orchestration (CARO) framework, an optimization-based approach that integrates multi-access edge computing (MEC) and network slicing to coordinate resource allocation across diverse service requirements. CARO employs a modular orchestration stack comprising a Slice Orchestrator for slice admission and prioritization, a MEC Controller for host selection and resource allocation, an SDN Controller for path selection, an NFV Orchestrator and VNF Manager for VNF lifecycle management, and a Physical Tier for dynamic infrastructure execution. By leveraging software-defined networking and network function virtualization, CARO dynamically prioritizes slices, selects MEC servers, and enforces QoS-aware policies, adapting to real-time network conditions and slice-aware workload consolidation. Simulation results from a 5G MEC scenario suggest that CARO can reduce average service delay for URLLC services and improve resource utilization compared with static allocation baselines. These results indicate that the proposed framework offers a practical way to balance scalability, adaptability, and operational efficiency in next-generation networks, while keeping orchestration overhead manageable.