How far can we go? Towards Realistic Software-Defined Wireless Networking Experiments

International audienceSoftware-Defined Wireless Networking (SDWN) is an emerging approach based on decoupling radio control functions from the radio data plane through programmatic interfaces. Despite diverse ongoing efforts to realize the vision of SDWN, many questions remain open from multiple perspectives such as means to rapid prototype and experiment candidate software solutions applicable to real world deployments. To this end, emulation of SDWN has the potential to boost research and development efforts by re-using existing protocol and application stacks while mimicking the behavior of real wireless networks. In this article, we provide an in-depth discussion on that matter focusing on the Mininet-WiFi emulator design to fill a gap in the experimental platform space. We showcase the applicability of our emulator in an SDN wireless context by illustrating the support of a number of use cases aiming to address the question on how far we can go in realistic SDWN experiments, including comparisons to the results obtained in a wireless testbed. Finally, we discuss the ability to replay packet-level and radio signal traces captured in the real testbed towards a virtual yet realistic emulation environment in support of SDWN research

How far can we go? towards realistic software-defined wireless networking experiments

Software-Defined Wireless Networking (SDWN) is an emerging approach based on decoupling radio control functions from the radio data plane through programmatic interfaces. Despite diverse ongoing efforts to realize the vision of SDWN, many questions remain open from multiple perspectives such as means to rapid prototype and experiment candidate software solutions applicable to real-world deployments. To this end, emulation of SDWN has the potential to boost research and development efforts by re-using existing protocol and application stacks while mimicking the behavior of real wireless networks. In this article, we provide an in-depth discussion on that matter focusing on the Mininet-WiFi emulator design to fill a gap in the experimental platform space. We showcase the applicability of our emulator in an SDN wireless context by illustrating the support of a number of use cases aiming to address the question on how far we can go in realistic SDWN experiments, including comparisons with the results obtained in a wireless testbed. Finally, we discuss the ability to replay packet-level and radio signal traces captured in the real testbed toward a virtual yet realistic emulation environment in support of SDWN research6010Section B: computer and communications networks and systems14581471FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP14/18482–4The R2lab wireless testbed at Inria has been funded by the ANR Equipex FIT 616

Optimization of a wifi wireless network that maximizes the level of satisfaction of users and allows the use of new technological trends in higher education institutions

The campus wireless networks have many users, who have different roles and network requirements, ranging from the use of educational platforms, informative consultations, emails, among others. Currently due to the inefficient use of network resources and little wireless planning, caused by the growth of the technological infrastructure (which is often due to daily worries, rather than to a lack of preparation by those in charge of managing the network), There are two essential factors that truncate the requirement of having a stable and robust net-work platform. First, the degradation of the quality of services perceived by users, and second, the congestion caused by the high demand for convergent traffic (video, voice, and data). Both factors imply great challenges on the part of the administrators of the network, which in many occasions are overwhelmed by per-manent incidences of instability, coverage, and congestion, as well as the diffi-culty of maintaining it economically. The present investigation seeks to propose a process of optimization of the infrastructure and parameters of the configuration of a wireless network, that allows maximizing the level of satisfaction of the users in Higher Education Institutions. In the first place, it is expected to determine an adequate methodology to estimate the level of satisfaction of the users (defining a mathematical criterion or algorithm based on the study variables [1], character-ize the environment in which the project will be developed, making a complete study of the wireless conditions and implement optimization strategies with soft-ware-defined networks (SDN). SDN is a concept in computer networks that al-lows network management to be carried out efficiently and flexibly, separating the control plane from the data plane into network devices. SDN architecture consists of an infrastructure layer which is a collection of network devices con-nected to the SDN Controller using protocol (OpenFlow) as a protocol [2]. Also, SDN will study traffic patterns on the network as a basis for optimizing network device usage [3]. The phases of the research will be carried out following the life cycle defined by the Cisco PPDIOO methodology (Prepare, Plan, Design, Imple-ment, Operate, Optimize) [4].Institución Universitaria ITSA, Corporación Universitaria Reformada CUR, Corporación Universitaria Latinoamericana CUL, Universidad de la Costa CUC, Universitaria Minuto de Dios UNIMINUTO, Universidad Libre

Impact of Docker Container Virtualization On Wireless Mesh Network by Using Software-Defined Network

In today’s advanced digital world era, it is extremely difficult for small enterprises or organizations to merge traditional or legacy computer network devices/equipment and wireless mesh networking devices with the latest digital computer network technology with respect to the expense of buying and maintaining expensive branded networking devices. However, today, by applying the neatly Software-defined networking, the OpenFlow protocol along with virtualization such as docker containers, which is a pack of their specific libraries, configured files, and software, provides advantages over proprietary or branded computer networking devices with respect to purchasing expenditure, operational expenditure, and improved performance in computer networking. Redistribution of routing protocol is very essential when using various autonomous systems in wireless mesh networks. Docker containers of frr and quagga give an edge over traditional or branded physical router devices, some docker containers are used as wired and wireless hosts/clients in the wireless mesh network. The novel idea used in this paper is on how to use the different software-defined controllers (Ryu and Pox controller) in a docker containerized wireless mesh network to analyse with respect to packet transfer, jitter in transmission, minimum delay in transmission, maximum delay in transmission, the average delay in transmission,  delay standard deviation bit-rate, send packets,  average packets drop, dropped packets along-with average loss-burst size in Mininet Wi-Fi testbed at the different scenario and the result shows that by using the docker container virtualization along with software-defined network two different controllers improves the performance and optimize the wireless mesh network. In addition, it shows that by using containerization and virtualization, capital expenditure and operational expenditure can be reduced in designing and developing wireless mesh network topologies.&nbsp

A step towards runnable papers using R2lab

In this paper, we present R2lab, an open, electromagnetically insulated research testbed dedicated to wireless networking. We describe the hardware capabilities currently available in terms of Software Defined Radio, and the software suite made available to deploy experiments. Taking as a pretext a dummy experiment, we show how it all fits into a notebook-based approach to getting closer to runnable papers

Modelado de Redes SDN con MININET

[ES] Las deficiencias que presentan las arquitecturas actuales en el diseño de redes frente a la aparición de nuevas tecnologías que necesitan de un mejor control del ancho de banda de la red y una mejora en la gestión de estas ha provocado la aparición de las redes SDN. Esta nueva arquitectura centraliza la lógica que gestiona el tráfico de la red a diferencia de otros modelos. Durante el siguiente proyecto se ha estudiado esta nueva arquitectura de red y los beneficios que aporta, además de observar mediante experimentación en el emulador Mininet-wifi el comportamiento de red de este. Pudiendo evaluar también el funcionamiento de este emulador.[EN] The deficiencies presented by the current architectures in the design of networks against the appearance of modern technologies that need a better control of the bandwidth of the network and an improvement in the management of these has caused the emergence of SDN networks. This new architecture centralizes the logic that manages the traffic of the network unlike other models. During the next project has studied this new network architecture and the benefits it provides, besides observing through experimentation in the emulator Mininet-wifi network behavior of this. You can also evaluate the operation of this emulator.Navarro Ojeda, FJ. (2017). Modelado de Redes SDN con MININET. http://hdl.handle.net/10251/88418.TFG

Implementación de redes definidas por software (SDN) sobre redes IEEE 802.11 mediante MININET WI-FI

El principal objetivo del presente trabajo fue la implementación de redes definidas por software (SDN) sobre redes IEEE 802.11 mediante Mininet Wi-Fi. Se recurrió a herramientas empleadas por las redes SDN para implementar enlaces inalámbricos y movilidad de hosts; se definieron conceptos básicos como: arquitectura SDN, protocolo OpenFlow, Mininet Wi-Fi y su eje principal el controlador. El controlador de SDN empleado fue OpenDayLight de Código Abierto; el cual ayuda a programar los caminos que seguirán los flujos de datos a lo largo de la red de una manera eficiente. La red fue simulada mediante el software Mininet Wi-Fi, emulador de Redes Inalámbricas Definidas por Software (SDWN). Los escenarios de pruebas fueron programados en lenguaje Python, a través de la consola de comandos de Mininet Wi-Fi. Se empleó la herramienta Wireshark para llevar a cabo capturas del tráfico en diversas interfaces, y conjuntamente con la herramienta iperf3 se envían flujos de datos TCP y UDP para obtener ancho de banda, perdida de datagramas, jitter en los enlaces de la red. Al realizar las pruebas respectivas para el escenario con los modelos de movilidad, se obtuvo que, en los modelos ReferencePoint y RandomWalk se generó un jitter de 5,64ms y 5,7ms, respectivamente, y valores de 0.73% y 0% en la pérdida de datagramas, debido a que RandomWalk crea patrones de movilidad más realistas y flexibles, mientras que ReferencePoint crea patrones de comportamiento grupal. Se concluye que al emplear un nuevo modelo de redes fue posible la implementación de soluciones eficientes para mejorar las redes inalámbricas; al optimizar un mayor despliegue de servicios y mejorar el rendimiento de las aplicaciones en toda la red.The main objective of this work was the implementation of software defined networks (SDN) over IEEE 802.11 networks through Mininet Wi-Fi. It was resorted to tools used by SDN networks to carry out wireless links and station mobility; basic concepts were defined such as: SDN architecture, OpenFlow protocol, Mininet Wi-Fi and its main axis, the controller. The SDN driver was OpenDayLight Open Source which helps to reprogram paths that will follow the data flows throughout the network in an efficient way. The network was simulated by using the software Mininet Wi-Fi, emulator of Wireless Networks Defined by software (SDWN). The test scenarios were programmed in Python language, through the command console of Mininet Wi-Fi. The Wireshark tool was used to carry out traffic captures in various interfaces, and together with the iperf3 tool, TCP and UDP data streams were sent to obtain bandwidth, datagram loss, and jitter in the network links. When performing the respective tests for the scenario with the mobility models, it was obtained that in the ReferencePoint and RandomWalk models a jitter of 5.64ms and 5.7ms was generated, respectively, and values of 0.73% and 0% in the loss of datagrams, because RandowWalk creates patterns of group behavior. It is concluded that, by using a new network model, it was possible to implement efficient solutions to improve wireless networks; by optimizing a greater deployment of services and improving the performance of applications throughout the network