Looking Glass of NFV: Inferring the Structure and State of NFV Network from External Observations

Abstract

The rapid development of network function virtualization (NFV) enables a communication network to provide in-network services using virtual network functions (VNFs) deployed on general IT hardware. While existing studies on NFV focused on how to provision VNFs from the provider's perspective, little is done about how to validate the provisioned resources from the user's perspective. In this work, we take a first step towards this problem by developing an inference framework designed to 'look into' the NFV network. Our framework infers the structure and state of the overlay formed by VNF instances, ingress/egress points of measurement flows, and critical points on their paths (branching/joining points). Our solution only uses external observations such as the required service chains and the end-to-end performance measurements. Besides the novel application scenario, our work also fundamentally advances the state of the art on topology inference by considering (i) general topologies with general measurement paths, and (ii) information of service chains. Our evaluations show that the proposed solution significantly improves both the reconstruction accuracy and the inference accuracy over existing solutions, and service chain information is critical in revealing the structure of the underlying topology.