Cost-Aware VNF Decomposition for VNF Forwarding Graph Embedding

To implement a Network Service (NS) within a Network Function Virtualization (NFV) environment, it is essential to create a sequence of connected Virtual Network Functions (VNFs), known as a VNF Forwarding Graph (VNF-FG), and then embed it onto the substrate network. The emergence of VNF decomposition as a new functional architecture allows VNFs to be broken down into smaller sub-functions, offering enhanced flexibility, resource sharing, and scalability. VNF decomposition can significantly reduce VNF embedding costs since different sub-functions can be efficiently reused by multiple network requests. However, when VNFs are decomposed into multiple sub-functions, selecting the appropriate decomposition option for each VNF and constructing the VNF-FG to embed onto the substrate network poses a significant challenge in NFV resource allocation (NFV-RA). A key challenge is identifying the optimal decomposition option among all possible choices for VNF embedding. In this paper, we introduce a cost-aware algorithm designed to address the topological decomposition of VNF-FGs, focusing on minimizing embedding costs while meeting specified service requirements. We formulate the VNF topology decomposition problem using Integer Linear Programming (ILP) to select the best decomposition option and minimize the embedding cost. Furthermore, we propose four efficient heuristics for different topologies to identify the optimal decomposition options for network embedding. Simulation results demonstrate that our proposed algorithm outperforms existing benchmarks in terms of embedding costs and achieves execution times that are up to 95% better than the SE approach.