On the Latency Benefits of Edge NFV

Next-generation networks are expected to support low-latency, context-aware and user-specific services in a highly flexible and efficient manner. Proposed applications include high-definition, low-latency video streaming, remote surgery, as well as applications for tactile Internet, virtual or augmented reality that demand network side data processing (such as image recognition, transformation or head/eye motion aware rendering). One approach to support these use cases is to introduce virtualized network services at the edge of the network, in close proximity of the end users to reduce end-to-end latency, time-to-response and unnecessary utilization of the core network, while providing flexibility for resource allocation. While many research projects including our previous work on Glasgow Network Functions have proposed running virtual network functions (vNF)s at the network edge, a latency-optimal placement allocation has not been presented before for the network edge and therefore the impact on user-to-vNF latency has not been investigated. In this paper, we formulate a simple vNF placement problem that minimizes end-to-end latency from users to their network functions. We have implemented the problem using Integer Linear Programming (ILP) with the Gurobi solver, and evaluated it with a real topology of a network provider. We use our solution to compare two vNF deployment scenarios over an emulation of a national backbone network: a two-tier edge deployment and a cloud-only deployment. We show that, in our example, using edge servers can deliver up to 70% improvement in user-to-vNF latency.