Reliability-aware hybrid SFC backup and deployment in edge computing

Abstract

As key enabling technologies for 5G, network function virtualization (NFV) abstracts services into software-based network function chains called service function chains (SFCs), greatly simplifying service management, while edge computing pushes compute resources to the edge close to IoT users, enabling low-latency services. For mission-critical applications, backup is an effective way to enhance the reliability of deployed SFCs. However, existing backup and deployment schemes mainly focus on off-site backups, neglecting on-site backups and resulting in suboptimal solutions. This paper investigates the problem of reliable SFC hybrid backup and deployment, aiming to minimize resource costs while accounting for limited edge resources and the heterogeneity of software reliability, hardware reliability, and resource charging. To tackle this problem, we first establish the mathematical association between backup and deployment decisions and these factors, formalize it as an integer nonlinear programming problem, and analyze its complexity. Then, we devise a bi-criteria approximation algorithm with rigorous theoretical guarantees, which relaxes the formalized problem to a convex optimization and rounds the fractional solution obtained by solving this convex optimization based on our insight, which approaches the optimal solution with bounded resource capacity violation, and is suitable for scenarios where moderate resource over-allocation is allowed. For cases prohibiting over-allocation, we propose a priority-guided algorithm with rigorous theoretical guarantees based on our insights, which prioritizes deploying backups for VNFs with the lowest reliability on edge sites that bring higher reliability improvements and lower charges. Extensive evaluation results show that our algorithm can save costs by up to 60.3% compared with state-of-the-art solutions.