Deploying elastic routing capability in an SDN/NFV-enabled environment

SDN and NFV are two paradigms that introduce unseen flexibility in telecom networks. Where previously telecom services were provided by dedicated hardware and associated (vendor-specific) protocols, SDN enables to control telecom networks through specialized software running on controllers. NFV enables highly optimized packet-processing network functions to run on generic/multi-purpose hardware such as x86 servers. Although the possibilities of SDN and NFV are well-known, concrete control and orchestration architectures are still under design and few prototype validations are available. In this demo we demonstrate the dynamic up-and downscaling of an elastic router supporting NFV-based network management, for example needed in a VPN service. The framework which enables this elasticity is the UNIFY ESCAPE environment, which is a PoC following an ETSI NFV MANO-conform architecture. This demo is one of the first to demonstrate a fully closed control loop for scaling NFs in an SDN/NFV control and orchestration architecture

Managing NFV using SDN and control theory

Control theory and SDN (Software Defined Networking) are key components for NFV (Network Function Virtualization) deployment. However little has been done to use a control-theoretic approach for SDN and NFV management. In this paper, we describe a use case for NFV management using control theory and SDN. We use the management architecture of RINA (a clean-slate Recursive InterNetwork Architecture) to manage Virtual Network Function (VNF) instances over the GENI testbed. We deploy Snort, an Intrusion Detection System (IDS) as the VNF. Our network topology has source and destination hosts, multiple IDSes, an Open vSwitch (OVS) and an OpenFlow controller. A distributed management application running on RINA measures the state of the VNF instances and communicates this information to a Proportional Integral (PI) controller, which then provides load balancing information to the OpenFlow controller. The latter controller in turn updates traffic flow forwarding rules on the OVS switch, thus balancing load across the VNF instances. This paper demonstrates the benefits of using such a control-theoretic load balancing approach and the RINA management architecture in virtualized environments for NFV management. It also illustrates that GENI can easily support a wide range of SDN and NFV related experiments

Scalable and Cost Efficient Algorithms for Virtual CDN Migration

Virtual Content Delivery Network (vCDN) migration is necessary to optimize the use of resources and improve the performance of the overall SDN/NFV-based CDN function in terms of network operator cost reduction and high streaming quality. It requires intelligent and enticed joint SDN/NFV migration algorithms due to the evident huge amount of traffic to be delivered to end customers of the network. In this paper, two approaches for finding the optimal and near optimal path placement(s) and vCDN migration(s) are proposed (OPAC and HPAC). Moreover, several scenarios are considered to quantify the OPAC and HPAC behaviors and to compare their efficiency in terms of migration cost, migration time, vCDN replication number, and other cost factors. Then, they are implemented and evaluated under different network scales. Finally, the proposed algorithms are integrated in an SDN/NFV framework. Index Terms: vCDN; SDN/NFV Optimization; Migration Algorithms; Scalability Algorithms.Comment: 9 pages, 11 figures, 4 tableaux, conference Local Computer Networks (LCN), class

Automated Network Service Scaling in NFV: Concepts, Mechanisms and Scaling Workflow

Next-generation systems are anticipated to be digital platforms supporting innovative services with rapidly changing traffic patterns. To cope with this dynamicity in a cost-efficient manner, operators need advanced service management capabilities such as those provided by NFV. NFV enables operators to scale network services with higher granularity and agility than today. For this end, automation is key. In search of this automation, the European Telecommunications Standards Institute (ETSI) has defined a reference NFV framework that make use of model-driven templates called Network Service Descriptors (NSDs) to operate network services through their lifecycle. For the scaling operation, an NSD defines a discrete set of instantiation levels among which a network service instance can be resized throughout its lifecycle. Thus, the design of these levels is key for ensuring an effective scaling. In this article, we provide an overview of the automation of the network service scaling operation in NFV, addressing the options and boundaries introduced by ETSI normative specifications. We start by providing a description of the NSD structure, focusing on how instantiation levels are constructed. For illustrative purposes, we propose an NSD for a representative NS. This NSD includes different instantiation levels that enable different ways to automatically scale this NS. Then, we show the different scaling procedures the NFV framework has available, and how it may automate their triggering. Finally, we propose an ETSI-compliant workflow to describe in detail a representative scaling procedure. This workflow clarifies the interactions and information exchanges between the functional blocks in the NFV framework when performing the scaling operation.Comment: This work has been accepted for publication in the IEEE Communications Magazin

Self-Modeling Based Diagnosis of Software-Defined Networks

Networks built using SDN (Software-Defined Networks) and NFV (Network Functions Virtualization) approaches are expected to face several challenges such as scalability, robustness and resiliency. In this paper, we propose a self-modeling based diagnosis to enable resilient networks in the context of SDN and NFV. We focus on solving two major problems: On the one hand, we lack today of a model or template that describes the managed elements in the context of SDN and NFV. On the other hand, the highly dynamic networks enabled by the softwarisation require the generation at runtime of a diagnosis model from which the root causes can be identified. In this paper, we propose finer granular templates that do not only model network nodes but also their sub-components for a more detailed diagnosis suitable in the SDN and NFV context. In addition, we specify and validate a self-modeling based diagnosis using Bayesian Networks. This approach differs from the state of the art in the discovery of network and service dependencies at run-time and the building of the diagnosis model of any SDN infrastructure using our templates

Network Functions Virtualization Architecture for Gateways for Virtualized Wireless Sensor and Actuator Networks

Virtualization enables multiple applications to share the same wireless sensor and actuator network (WSAN). However, in heterogeneous environments, virtualized wireless sensor and actuator networks (VWSAN) raise new challenges, such as the need for on-the-fly, dynamic, elastic, and scalable provisioning of gateways. Network Functions Virtualization (NFV) is a paradigm emerging to help tackle these new challenges. It leverages standard virtualization technology to consolidate special-purpose network elements on commodity hardware. This article presents NFV architecture for VWSAN gateways, in which software instances of gateway modules are hosted in NFV infrastructure operated and managed by a VWSAN gateway provider. We consider several VWSAN providers, each with its own brand or combination of brands of sensors and actuators/robots. These sensors and actuators can be accessed by a variety of applications, each may have different interface and QoS (i.e., latency, throughput, etc.) requirements. The NFV infrastructure allows dynamic, elastic, and scalable deployment of gateway modules in this heterogeneous VWSAN environment. Furthermore, the proposed architecture is flexible enough to easily allow new sensors and actuators integration and new application domains accommodation. We present a prototype that is built using the OpenStack platform. Besides, the performance results are discusse