Delay-constrained NFV orchestration for heterogeneous cloud networks

Abstract

Recently, network services are increasingly connecting computational elements within and across datacenters. In the Network Functions Virtualization (NFV) environment, to successfully orchestrate a network service, first a VNF-Forwarding Graph (VNF-FG) must be composed that realizes the required functionality. Second, this VNF-FG must be embedded onto the infrastructure, that is increasingly becoming heterogeneous. To efficiently allocate service demands, intelligent mechanisms and algorithms are needed to effectively tailor the VNF-FG to the cloud network onto which the service will be deployed. This paper introduces the first service model supporting on-demand orchestration of services with bidirectional chaining and delay constraints, optional VNFs and traffic aggregation. Building on this service model, we propose algorithms looking for the optimization of the order and number of VNF instances, to adapt the VNF-FG to the available resources in the substrate network. Numerical experiments show that, through coordination of composition and embedding tasks, our proposed algorithms can significantly improve the acceptance ratio, compared to algorithms that perform these tasks in two separate stages.