Affinity measurement for NFV-enabled networks: A criteria-based approach

Network Functions Virtualization (NFV) offers several benefits for Service Providers (SPs), such as mitigating equipment cost and increasing business agility. In NFV-enabled networks, inadequate placement of Virtualized Network Functions (VNFs) creates bottlenecks, impacting negatively on performance. Therefore, network operators must establish affinity and anti-affinity rules to avoid network and processing bottlenecks, and thus comply with Service Level Agreement (SLA) requirements of tenants. Affinity and anti-affinity rules in NFV must be broad and carefully elaborated to maintain service performance. Network operators must consider further than simply resource allocation when identifying affinity among VNFs. The criteria for VNFs affinity varies for different forwarding graphs. Geolocation, latency, packet loss, and bandwidth usage are some examples of criteria that can be considered as indicators of bottlenecks in high traffic networks. In this paper, we propose a solution to measure affinity between pairs of VNFs, based on a weighted set of affinity criteria considered relevant by a network operator. To evaluate the feasibility of our affinity model, we analyze three case studies over an experimental NFV scenario. We conclude that our affinity model can help network operators identify the cause of issues in NFV-enabled networks, as well as it may be used by NFV orchestrators to aid on VNFs migration and embedding.