Latency-Aware, Static, and Dynamic Decision-Tree Placement Algorithm for Containerized SDN-VNF in OpenFlow Architectures

Abstract

The preliminary work conducted as a part of this research evaluated two virtualization technologies, virtual machines (VM) and containers, for a software-defined networking controller virtual network function (SDN-VNF) – per the NFV Research Group (NFVRG) testing guidelines. Although the VNF benchmarking experiment results have proved that container-based VNFs offer various performance advantages (memory/throughput) over VM-based VNFs, prior work lacks the development of optimal containerized VNF placement algorithms. The goal of this research is to further the preliminary work that presented a resilient SDN/NFV infrastructure per ETSI-NFV design considerations that actively orchestrates and monitors the network infrastructure comprising of SDN-VNF by designing a decision-tree (DT) algorithm to perform an optimal placement of containerized SDN-VNFs in an OpenFlow network architecture. The research compares two approaches for implementing the DT algorithm – first, using cbench as the OpenFlow statistics advisor and second, using a northbound application as the OpenFlow statistics advisor. The result indicates that the DT algorithm offers comparatively smaller and near-constant total placement time when it is coupled with a northbound application compared to the former approach that uses cbench. Moreover, the second approach removes any OpenFlow switch Operating System (OS) dependency (that is required in case of cbench) which further benefits its adoption in multi-faceted OpenFlow networks. The outcome of this research enhances the body of knowledge on implementing optimal containerized SDN-VNF placement algorithms that facilitate Internet Service Providers (ISPs) understanding of the benefits of containerized SDN-VNF adoption.