SFC-ACO: A Robust Path Failure Handling Method for Service Function Chaining in Kubernetes on OpenStack Magnum

The increasing demand for scalable, flexible, and adaptable network infrastructures has led to the growing popularity of Network Function Virtualization (NFV) in modern networks. Virtual Network Functions (VNFs) and Cloud-Native Network Functions (CNFs) are virtualized network services that can be arranged in a specific sequence called Service Function Chaining (SFC). However, multiple path failures in the service function path pose a significant challenge for SFC. To address this issue, this research proposes an Improved Ant Colony Optimization (SFC-ACO) algorithm that integrates Mixed Integer Programming (MILP) constraints into the traditional Ant Colony Optimization (ACO) algorithm. The algorithm is implemented using Kubernetes Cluster with OpenStack Magnum. The proposed algorithm generates a path that meets CNF requirements while minimizing end-to-end delay and providing alternative paths in case of path failure. Experimental results demonstrate the effectiveness of the proposed algorithm in optimizing end-to-end delay compared to the generic ACO algorithm, highlighting its potential as a practical solution for network operators in 5G networks.