Availability-Aware VNF Placement and Request Routing in MEC-Enabled 5G Networks

2025-08-20

AI Summary

This paper addresses the joint optimization of Virtual Network Function (VNF) placement and request routing in 5G Mobile Edge Computing (MEC) to meet the ultra-reliable and low-latency communication (uRLLC) requirements, maximizing service provider revenue under end-to-end reliability and latency constraints. Method: We propose a synergistic solution framework integrating constrained optimization modeling, approximate randomized rounding, and greedy heuristic algorithms to effectively handle resource constraint violations and uncover the trade-off between availability and resource efficiency. Contribution/Results: The proposed algorithm achieves 95% and 90% of the optimal revenue, respectively. We implement an open-source 5G software prototype supporting VNF redundancy deployment; experiments demonstrate that redundancy significantly improves packet delivery ratio and reduces end-to-end latency.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

In this paper, we study the virtual network function (VNF) placement problem in mobile edge computing (MEC)-enabled 5G networks to meet the stringent reliability and latency requirements of uRLLC applications. We pose it as a constrained optimization problem, which is NP-hard, to maximize the total reward obtained by a network service provider by serving uRLLC service requests. We propose an approximated randomized rounding approach to solve the NP-hard optimization problem in polynomial time. We prove that the proposed randomized approach achieves performance guarantees while violating the resource constraints boundedly. Furthermore, we present a greedy-heuristic approach to tackle the violations of resource constraints. Simulation results show that the proposed randomized rounding and greedy approaches achieve a total reward which is within 5% and 10% of the optimal solution, respectively. Furthermore, we compare the proposed greedy approach with the existing schemes that do not consider the availability requirements. We observe that the existing schemes perform poorly in terms of total reward, as negligence to the availability requirements negatively impacts the number of successfully served requests. These findings highlight the trade-off between availability and resource efficiency in latency-sensitive uRLLC applications. We also implement a software prototype of a 5G network using open-source software platforms with redundant placement of VNFs. The results on packet delivery ratio and latency obtained from the prototype implementation are also improved in the redundant VNFs with different failure probabilities.

Problem

• Optimizing VNF placement for uRLLC reliability and latency requirements
• Solving NP-hard constrained optimization for service provider reward maximization
• Addressing availability-resource efficiency tradeoff in 5G MEC networks

Innovation

• Randomized rounding for NP-hard optimization
• Greedy-heuristic for resource constraint violations
• Redundant VNF placement for availability requirements