Experimental proof of concept of an SDN-based traffic engineering solution for hybrid satellite-terrestrial mobile backhauling

This is the peer reviewed version of the following article: Mendoza, F, Ferrus, R, Sallent, O. Experimental proof of concept of an SDN‐based traffic engineering solution for hybrid satellite‐terrestrial mobile backhauling. Int J Satell Commun Network. 2019; 37: 630– 645, which has been published in final form at https://doi.org/10.1002/sat.1303. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-ArchivingSatellite networks are expected to be an integral part of 5G service deployment. One compelling use case is mobile backhauling, where the exploitation of a satellite component can improve the reach, robustness, and economics of 5G rollout. The envisaged availability of new satellite capacity, together with the development of better integration approaches for the provisioning and operation of the satellite component in a more flexible, agile, and cost-effective manner than done today, are expected to revamp such use case within the 5G ecosystem. In this context, sustained in the architectural designs proposed within H2020 VITAL research project, this paper presents an experimental proof of concept (PoC) of a satellite-terrestrial integration solution that builds upon software-defined networking (SDN) technologies for the realization of end-to-end traffic engineering (E2E TE) in mobile backhauling networks with a satellite component. A laboratory test bed has been developed and validated, consisting of a small-scale private mobile network with a backhaul setting that combines Ethernet-wired links, a satellite link emulator (OpenSAND), OpenFlow switches, and an OpenFlow controller running the network application for E2E TE. Provided results show the operation of a E2E TE application able to enforce different traffic routing and path failure restoration policies as well as the performance impact that it has on the mobile network connectivity services.Peer ReviewedPostprint (author's final draft

Comparison of WLAN Probe and Light Sensor-Based Estimators of Bus Occupancy Using Live Deployment Data

Bus company operators are interested in obtaining knowledge about the number of passengers on their buses—preferably doing so at low deployment costs and in an automated manner, while keeping accuracy high. One solution, widely used in practice, involves deploying a light sensor-based system, counting the people entering and leaving the bus. The light sensor system is simple, but errors accumulate over time, because it is not capable of error correcting. For this reason, the light sensor-based system is compared to a WLAN probe-based system, which has entirely different characteristics. Inaccuracy with the WLAN estimator comes from a need to filter out mobile devices outside the bus and to map the number of detected devices to a number of people. The comparison is performed based on data collected from a real-life deployment in a medium sized German city. The comparison shows the trade-off in selecting either of the two methods. Furthermore, a novel approach for fusion of the light sensor and WLAN estimators is proposed which has a big potential in improving accuracy of both estimators. A fusion approach is proposed that utilizes the different error characteristics for error compensation by calculating compensation terms. The knowledge of Ground Truth is not required as part of this fusion approach for calibration; results show that the approach can find the optimal parameter settings and that it makes this occupancy estimation approach scalable and automated

Data-driven analytics task management reasoning mechanism in edge computing

Internet of Things (IoT) applications have led to exploding contextual data for predictive analytics and exploration tasks. Consequently, computationally data-driven tasks at the network edge, such as machine learning models’ training and inference, have become more prevalent. Such tasks require data and resources to be executed at the network edge, while transferring data to Cloud servers negatively affects expected response times and quality of service (QoS). In this paper, we study certain computational offloading techniques in autonomous computing nodes (ANs) at the edge. ANs are distinguished by limited resources that are subject to a variety of constraints that can be violated when executing analytical tasks. In this context, we contribute a task-management mechanism based on approximate fuzzy inference over the popularity of tasks and the percentage of overlapping between the data required by a data-driven task and data available at each AN. Data-driven tasks’ popularity and data availability are fed into a novel two-stages Fuzzy Logic (FL) inference system that determines the probability of either executing tasks locally, offloading them to peer ANs or offloading to Cloud. We showcase that our mechanism efficiently derives such probability per each task, which consequently leads to efficient uncertainty management and optimal actions compared to benchmark models

Satellite integration in 5G : contribution on network architectures and traffic engineering solutions for hybrid satellite-terrestrial mobile backhauling

The recent technological advances in the satellite domain such as the use of High Throughput Satellites (HTS) with throughput rates that are magnitudes higher than with previous ones, or the use of large non- Geostationary Earth Orbit (GEO) satellites constellations, etc, are reducing the price per bit and enhancing the Quality of Service (QoS) metrics such as latency, etc., changing the way that the capacity is being brought to the market and making it more attractive for other services such as satellite broadband communications. These new capabilities coupled with the advantages offered by satellite communications such as the unique wide-scale geographical coverage, inherent broadcast/multicast capabilities and highly reliable connectivity, anticipate new opportunities for the integration of the satellite component into the 5G ecosystem. One of the most compelling scenarios is mobile backhauling, where satellite capacity can be used to complement the terrestrial backhauling infrastructure, not only in hard to reach areas, but also for more efficient traffic delivery to Radio Access Network (RAN) nodes, increased resiliency and better support for fast, temporary cell deployments and moving cells. In this context, this thesis work focuses on achieving better satellite-terrestrial backhaul network integration through the development of Traffic Engineering (TE) strategies to manage in a better way the dynamically steerable satellite provisioned capacity. To do this, this thesis work first takes the steps in the definition of an architectural framework that enables a better satellite-terrestrial mobile backhaul network integration, managing the satellite capacity as a constituent part of a Software Defined Networking (SDN) -based TE for mobile backhaul network. Under this basis, this thesis work first proposes and assesses a model for the analysis of capacity and traffic management strategies for hybrid satellite-terrestrial mobile backhauling networks that rely on SDN for fine-grained traffic steering. The performance analysis is carried out in terms of capacity gains that can be achieved when the satellite backhaul capacity is used for traffic overflow, taking into account the placement of the satellite capacity at different traffic aggregation levels and considering a spatial correlation of the traffic demand. Later, the thesis work presents the development of SDN-based TE strategies and algorithms that exploits the dynamically steerable satellite capacity provisioned for resilience purposes to better utilize the satellite capacity by maximizing the network utility under both failure and non-failure conditions in some terrestrial links, under the consideration of elastic, inelastic and unicast and multicast traffic. The performance analysis is carried out in terms of global network utility, fairness and connexion rejection rates compared to non SDN-based TE applications. Finally, sustained in the defined architectural framework designs, the thesis work presents an experimental Proof of Concept (PoC) and validation of a satellite-terrestrial backhaul links integration solution that builts upon SDN technologies for the realization of End-to-End (E2E) TE applications in mobile backhauling networks with a satellite component, assessing the feasibility of the proposed SDN-based integration solution under a practical laboratory setting that combines the use of commercial, experimentation-oriented and emulation equipment and software.Los recientes avances tecnológicos en el dominio de los satélites, como el uso de satélites de alto rendimiento (HTS) con tasas de rendimiento que son magnitudes más altas que los anteriores, o el uso de grandes constelaciones de satélites de órbita no geoestacionaria (GEO), etc. están reduciendo el precio por bit y mejorando las métricas de Calidad de Servicio (QoS) como la latencia, etc., cambiando la forma en que la capacidad se está llevando al mercado, y haciéndola más atractiva para otros servicios como las comunicaciones de banda ancha por satélite. Estas nuevas capacidades, junto con las ventajas ofrecidas por las comunicaciones por satélite, como la cobertura geográfica a gran escala, las inherentes capacidades de difusión / multidifusión y la conectividad altamente confiable, anticipan nuevas oportunidades para la integración de la componente satelital al ecosistema 5G. Uno de los escenarios más atractivos es el backhauling móvil, donde la capacidad del satélite se puede usar para complementar la infraestructura de backhauling terrestre, no solo en áreas de difícil acceso, sino también para la entrega de tráfico de manera más eficiente a los nodos de la Red de Acceso (RAN), una mayor resiliencia y mejor soporte para implementaciones rápidas y temporales de células, así como células en movimiento. En este contexto, este trabajo de tesis se centra en lograr una mejor integración de la red híbrida de backhaul satélital-terrestre, a través del desarrollo de estrategias de ingeniería de tráfico (TE) para gestionar de una mejor manera la capacidad dinámicamente orientable del satélite. Para hacer esto, este trabajo de tesis primero toma los pasos en la definición de un marco de arquitectura que permite una mejor integración de una red híbrida satelital-terrestre de backhaul móvil, gestionando la capacidad del satélite como parte constitutiva de un TE basado en Software Defined Networking (SDN). Bajo esta base, este trabajo de tesis primero propone y evalúa un modelo para el análisis de la capacidad y las estrategias de gestión del tráfico para redes híbridas satelital-terrestre de backhaul móvil basadas en SDN para la dirección de tráfico. El análisis de rendimiento se lleva a cabo en términos de aumento de capacidad que se puede lograr cuando la capacidad de la red de backhaul por satélite se utiliza para el desborde de tráfico, teniendo en cuenta la ubicación de la capacidad del satélite en diferentes niveles de agregación de tráfico y considerando una correlación espacial de la demanda de tráfico. Posteriormente, el trabajo de tesis presenta el desarrollo de estrategias y algoritmos de TE basados en SDN que explotan la capacidad dinámicamente orientable del satelite, provista con fines de resiliencia para utilizar de mejor manera la capacidad satelital al maximizar la utilidad de red en condiciones de falla y no falla en algunos enlaces terrestres, y bajo la consideración de tráfico elástico, inelástico y de unidifusión y multidifusión. El análisis de rendimiento se lleva a cabo en términos de tasas de rechazo, de utilidad, y equidad en comparación con las aplicaciones de TE no basadas en SDN. Finalmente, basado en la definición del diseño de marco de arquitectura, el trabajo de tesis presenta una Prueba de concepto (PoC) experimental y la validación de una solución de integración de enlaces de backhaul satelital-terrestre que se basa en las tecnologías SDN para la realización de aplicaciones de TE de extremo a extremo (E2E) en redes de backhaul móviles, evaluando la viabilidad de la solución propuesta de integración basada en SDN en un entorno práctico de laboratorio que combina el uso de equipos y software comerciales, orientados a la experimentación y emulación.Postprint (published version

Network Service Availability and Continuity Management in the Context of Network Function Virtualization

In legacy computer systems, network functions (e.g., routers, firewalls, etc.) have been provided by specialized hardware appliances to realize Network Services (NS). In recent years, the rise of Network Function Virtualization (NFV) has changed how we realize NSs. With NFV, commercial off-the-shelf hardware and virtualization technologies are used to create Virtual Network Functions (VNF). In the context of NFV, an NS is realized by interconnecting VNFs using Virtual Links (VL). Service availability and continuity are among the important non-functional characteristics of NSs. Availability is defined as the fraction of time the NS functionality is provided in a period. Current work on NS availability, in the NFV context, focuses on determining the appropriate number of redundant VNFs and their deployment in the virtualized environment, and the redundancy of network paths. Such solutions are necessary but insufficient because redundancy does not guarantee that the overall service outage time for an NS functionality remains below a certain threshold. Moreover, service disruption which impacts the service continuity is not addressed in the current work quantitatively. In addition, NSs and VNFs elasticity and the dynamicity of virtualized infrastructures which can impact the availability of NS functionalities, are not considered in the current state of the art. In this thesis, we propose a framework for NS availability and continuity management, which consists of two approaches, one for design time and another for runtime adaptation. For this, we define service disruption time for an NS functionality as the amount of time for which the service data is lost due to service outages for a given period. We also define the service data disruption for an NS functionality as the maximum amount of data lost due to a service outage. The design-time approach includes analytical methods which take acceptable service disruption and availability requirements of the tenant, a designed NS, and a given infrastructure as inputs to adjust the NS design and map these requirements to constraints on low-level configuration parameters. Design-time approach guarantees the service availability and continuity requirements will be met as long as the availability characteristics of the infrastructure resources used by the NS constituents do not change at runtime. However, changes in the supporting infrastructure may happen at runtime due to multiple reasons like failover, upgrades, and aging. Therefore, we propose a runtime adaptation approach that reacts to changes at runtime and adjusts the configuration parameters accordingly to satisfy the same service availability and continuity requirements. The runtime approach uses machine learning models, which are created at design time, to determine the required adjustments at runtime. To demonstrate the feasibility of the proposed solutions and to experiment with them, we present a proof of concept, including prototypes of our approaches and their application in a small NFV cloud environment created for validation purposes. We conduct multiple experiments for two case studies with different service availability and continuity requirements. The results from the conducted experiments show that our approaches can guarantee the fulfillment of the service availability and continuity requirements

Études des systèmes de communications sans-fil dans un environnement rural difficile

Les systèmes de communication sans fil, ayant de nombreux avantages pour les zones rurales, peuvent aider la population à bien s'y établir au lieu de déménager vers les centres urbains, accentuant ainsi les problèmes d’embouteillage, de pollution et d’habitation. Pour une planification et un déploiement efficace de ces systèmes, l'atténuation du signal radio et la réussite des liens d’accès doivent être envisagées. Ce travail s’intéresse à la provision d’accès Internet sans fil dans le contexte rural canadien caractérisé par sa végétation dense et ses variations climatiques extrêmes vu que les solutions existantes sont plus concentrées sur les zones urbaines. Pour cela, nous étudions plusieurs cas d’environnements difficiles affectant les performances des systèmes de communication. Ensuite, nous comparons les systèmes de communication sans fil les plus connus. Le réseau sans fil fixe utilisant le Wi-Fi ayant l’option de longue portée est choisi pour fournir les communications aux zones rurales. De plus, nous évaluons l'atténuation du signal radio, car les modèles existants sont conçus, en majorité, pour les technologies mobiles en zones urbaines. Puis, nous concevons un nouveau modèle empirique pour les pertes de propagation. Des approches utilisant l’apprentissage automatique sont ensuite proposées, afin de prédire le succès des liens sans fil, d’optimiser le choix des points d'accès et d’établir les limites de validité des paramètres des liens sans fil fiables. Les solutions proposées font preuve de précision (jusqu’à 94 % et 8 dB RMSE) et de simplicité, tout en considérant une multitude de paramètres difficiles à prendre en compte tous ensemble avec les solutions classiques existantes. Les approches proposées requièrent des données fiables qui sont généralement difficiles à acquérir. Dans notre cas, les données de DIGICOM, un fournisseur Internet sans fil en zone rurale canadien, sont utilisées. Wireless communication systems have many advantages for rural areas, as they can help people settle comfortably and conveniently in these regions instead of relocating to urban centers causing various overcrowding, habitation, and pollution problems. For effective planning and deployment of these technologies, the attenuation of the radio signal and the success of radio links must be precisely predicted. This work examines the provision of wireless internet access in the Canadian rural context, characterized by its dense vegetation and its extreme climatic variations, since existing solutions are more focused on urban areas. Hence, we study several cases of difficult environments affecting the performances of communication systems. Then, we compare the best-known wireless communication systems. The fixed wireless network using Wi-Fi, having the long-range option, is chosen to provide wireless access to rural areas. Moreover, we evaluate the attenuation of the radio signal, since the existing path loss models are generally designed for mobile technologies in urban areas. Then, we design a new path loss empirical model. Several approaches are then proposed by using machine learning to predict the success of wireless links, optimize the choice of access points and establish the validity limits for the pertinent parameters of reliable wireless connections. The proposed solutions are characterized by their accuracy (up to 94% and 8 dB RMSE) and simplicity while considering a wide range of parameters that are difficult to consider all together with conventional solutions. These approaches require reliable data, which is generally difficult to acquire. In our case, the dataset from DIGICOM, a rural Canadian wireless internet service provider, is used