Dynamic resource allocation for URLLC and eMBB in MEC-NFV 5G networks

Abstract

Supporting the coexistence between enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low Latency Communications (URLLC) is a major challenge in modern communication systems due to their diverse requirements. Multi-access Edge Computing (MEC), Network Function Virtualization (NFV), and Network Slicing (NS) emerge as complementary paradigms to address this challenge, providing fine-grained, on-demand resources closer to the User Equipment (UE) and enabling shared utilization of physical infrastructure. This paper addresses the combination of MEC, NFV, NS, and dynamic virtual resource allocation for overcoming the problem of resource dimensioning at the network edge supporting eMBB and URLLC services. We have proposed a Continuous-Time Markov Chain (CTMC) model to evaluate how requests are managed by the virtualization resources of a single MEC node, primarily focusing on fulfilling the requirements of both eMBB and URLLC services. It characterizes the dynamic virtual resource allocation process and incorporates three key performance metrics, relevant for both URLLC and eMBB services (e.g., availability and response time) as well as for service providers (e.g., power consumption). The model also integrates practical factors such as failures during service processing, service prioritization, and setup (repair) times, enabling insights into how the MEC-NFV-based 5G network handles different service categories by applying service prioritization and dynamic resource allocation. Our key findings reveal that container setup and failure rates play a crucial role in both availability and response times, higher setup rates improve availability and shorten response times. Additionally, the number of containers significantly enhances both metrics, whereas buffer sizes primarily influence response times. Furthermore, higher eMBB arrival rates reduce availability and increase response times, while URLLC availability remains unaffected.