QoSVisor: QoS Framework for SDN

The increasing demand for network services and quality across wide selections of digital applications in the internet era has caused growing congestion and raised questions about how to deal with prioritizing data in ways tailored to particular uses of applications and managing peak congestion times. Software Defined Network (SDN) in particular Slicing Strategy, seems the best solution due to its new constitution intelligently implemented through the SDN OpenFlow protocol. However, Slicing Strategies specifically “FlowVisor” are limited in certain mechanisms such as Traffic Engineering (TE), which make it a requirement to find new ways to deliver Quality of Service (QoS) for different applications. In this paper, QoSVisor presented as an SDN extension action QoS Slicer based as an enhancement to the standard FlowVisor operation slicing tools to ensure the QoS for each Slice-based class of application

NVP: A Network Virtualization Proxy for Software Defined Networking

The combination of Network Function Virtualization (NFV) and Software Defined Networking (SDN) can improve the control and utilization of network resources. However, this issue still requires proper solutions to virtualize large-scale networks, which would allow the use of SDN and Virtualization in real environments.Thus, this paper proposes a virtualization architecture for SDN that relies on a proxy-based approach. The NVP (Network Virtualization Proxy) is a virtualization proxy that intercepts messages exchanged between controllers and switches SDN enabling network virtualization. An implementation of the proposal was developed as a proof of concept and load testing was performed showing that the solution can provide network virtualization in a scalable manner, using less than 2.5 MB of memory to manage 100 switches performing simultaneous requests, whereas FlowVisor requires more than 200 MB

On the Benefit of Virtualization: Strategies for Flexible Server Allocation

Virtualization technology facilitates a dynamic, demand-driven allocation and migration of servers. This paper studies how the flexibility offered by network virtualization can be used to improve Quality-of-Service parameters such as latency, while taking into account allocation costs. A generic use case is considered where both the overall demand issued for a certain service (for example, an SAP application in the cloud, or a gaming application) as well as the origins of the requests change over time (e.g., due to time zone effects or due to user mobility), and we present online and optimal offline strategies to compute the number and location of the servers implementing this service. These algorithms also allow us to study the fundamental benefits of dynamic resource allocation compared to static systems. Our simulation results confirm our expectations that the gain of flexible server allocation is particularly high in scenarios with moderate dynamics

Development of a performance measurement tool for SDN

The project wants to develop a tool to measure link latency from a OpenFlow controller. It uses Mininet, a software to emulate SDN computer network, and POX as controller

Software-Defined Networks for Future Networks and Services: Main Technical Challenges and Business Implications

In 2013, the IEEE Future Directions Committee (FDC) formed an SDN work group to explore the amount of interest in forming an IEEE Software-Defined Network (SDN) Community. To this end, a Workshop on "SDN for Future Networks and Services" (SDN4FNS'13) was organized in Trento, Italy (Nov. 11th-13th 2013). Following the results of the workshop, in this paper, we have further analyzed scenarios, prior-art, state of standardization, and further discussed the main technical challenges and socio-economic aspects of SDN and virtualization in future networks and services. A number of research and development directions have been identified in this white paper, along with a comprehensive analysis of the technical feasibility and business availability of those fundamental technologies. A radical industry transition towards the "economy of information through softwarization" is expected in the near future

A proposal for secured, efficient and scalable layer 2 network virtualisation mechanism

El contenidos de los capítulos 3 y 4 está sujeto a confidencialidad. 291 p.La Internet del Futuro ha emergido como un esfuerzo investigador para superar estas limitaciones identificadas en la actual Internet. Para ello es necesario investigar en arquitecturas y soluciones novedosas (evolutivas o rompedoras), y las plataformas de experimentación surgen para proporcionar un entorno realista para validar estas nuevas propuestas a gran escala.Debido a la necesidad de compartir la misma infraestructura y recursos para testear simultáneamente diversas propuestas de red, la virtualización de red es la clave del éxito. Se propone una nueva taxonomía para poder analizar y comparar las diferentes propuestas. Se identifican tres tipos: el Nodo Virtual (vNode), la Virtualización posibilitada por SDN (SDNeV) y el overlay.Además, se presentan las plataformas experimentales más relevantes, con un foco especial en la forma en la que cada una de ellas permite la investigación en propuestas de red, las cuales no cumplen todos estos requisitos impuestos: aislamiento, seguridad, flexibilidad, escalabilidad, estabilidad, transparencia, soporte para la investigación en propuestas de red. Por lo tanto, una nueva plataforma de experimentación ortogonal a la experimentación es necesaria.Las principales contribuciones de esta tesis, sustentadas sobre tecnología SDN y NFV, son también los elementos clave para construir la plataforma de experimentación: la Virtualización de Red basada en Prefijos de Nivel 2 (Layer 2 Prefix-based Network Virtualisation, L2PNV), un Protocolo para la Configuración de Direcciones MAC (MAC Address Configuration Protocol, MACP), y un sistema de Control de Acceso a Red basado en Flujos (Flow-based Network Access Control, FlowNAC).Como resultado, se ha desplegado en la Universidad del Pais Vasco (UPV/EHU) una nueva plataforma experimental, la Plataforma Activada por OpenFlow de EHU (EHU OpenFlow Enabled Facility, EHU-OEF), para experimentar y validar estas propuestas realizadas

Machine learning-based routing and wavelength assignment in software-defined optical networks

Recently, machine learning (ML) has attracted the attention of both researchers and practitioners to address several issues in the optical networking field. This trend has been mainly driven by the huge amount of available data (i.e., signal quality indicators, network alarms, etc.) and to the large number of optimization parameters which feature current optical networks (such as, modulation format, lightpath routes, transport wavelength, etc.). In this paper, we leverage the techniques from the ML discipline to efficiently accomplish the routing and wavelength assignment (RWA) for an input traffic matrix in an optical WDM network. Numerical results show that near-optimal RWA can be obtained with our approach, while reducing computational time up to 93% in comparison to a traditional optimization approach based on integer linear programming. Moreover, to further demonstrate the effectiveness of our approach, we deployed the ML classifier into an ONOS-based software defined optical network laboratory testbed, where we evaluate the performance of the overall RWA process in terms of computational time.The authors would like to acknowl-edge the support of the project TEXEO (TEC2016-80339-R), funded by Spanish MINECO and the EU-H2020 Metrohaul project (grant no. 761727)