Online VNF Placement and Chaining for Value-added Services in Content Delivery Networks

TL;DR

This paper addresses the challenge of online placement and reconfiguration of Virtual Network Function Forwarding Graphs for value-added services in Content Delivery Networks, aiming to minimize costs while maintaining quality of service.

Contribution

It introduces an ILP-based model for online VNF-FG placement considering reuses, migrations, and multiple costs, which is a novel approach compared to offline methods.

Findings

ILP model effectively minimizes reconfiguration costs.

Online placement adapts to changing service usage patterns.

Small-scale scenario evaluation demonstrates feasibility.

Abstract

Value-added Services (VASs) (e.g. dynamic site acceleration, media management) play a critical role in Content Delivery Networks (CDNs). Network Functions Virtualization (NFV) enables the agile provisioning of VASs. In NFV settings, VASs are provisioned as ordered sets of Virtual Network Functions (VNFs), forming VNF-Forwarding Graphs (VNF-FG) which are deployed in the CDN infrastructure. The CDN VAS VNF-FGs have a specific characteristic: they have one end-point (corresponding to the content server) that is unknown, prior to their placement. The proposals for CDN VAS VNF-FG placement, so far, have only considered offline placement, where the VNF-FGs are placed before end-user traffic steers into the network. However, in concrete cases, a change in service usage patterns might occur, a situation that could require a VNF-FG placement in an online manner. This paper tackles the problem of online VNF-FG placement for VASs in CDNs, taking into account the eventual reuses and migrations of already-deployed VNFs. A cost model is considered, including multiple costs; i.e. new VNF instantiations, migration, hosting and routing costs. The objective is to optimally place the VNF-FGs such that total reconfiguration costs are minimized while QoS is satisfied. An Integer Linear Programming (ILP) formulation is provided and evaluated in a small-scale scenario.