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

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

Measurement-Driven Algorithm and System Design for Wireless and Datacenter Networks

The growing number of mobile devices and data-intensive applications pose unique challenges for wireless access networks as well as datacenter networks that enable modern cloud-based services. With the enormous increase in volume and complexity of traffic from applications such as video streaming and cloud computing, the interconnection networks have become a major performance bottleneck. In this thesis, we study algorithms and architectures spanning several layers of the networking protocol stack that enable and accelerate novel applications and that are easily deployable and scalable. The design of these algorithms and architectures is motivated by measurements and observations in real world or experimental testbeds. In the first part of this thesis, we address the challenge of wireless content delivery in crowded areas. We present the AMuSe system, whose objective is to enable scalable and adaptive WiFi multicast. AMuSe is based on accurate receiver feedback and incurs a small control overhead. This feedback information can be used by the multicast sender to optimize multicast service quality, e.g., by dynamically adjusting transmission bitrate. Specifically, we develop an algorithm for dynamic selection of a subset of the multicast receivers as feedback nodes which periodically send information about the channel quality to the multicast sender. Further, we describe the Multicast Dynamic Rate Adaptation (MuDRA) algorithm that utilizes AMuSe's feedback to optimally tune the physical layer multicast rate. MuDRA balances fast adaptation to channel conditions and stability, which is essential for multimedia applications. We implemented the AMuSe system on the ORBIT testbed and evaluated its performance in large groups with approximately 200 WiFi nodes. Our extensive experiments demonstrate that AMuSe can provide accurate feedback in a dense multicast environment. It outperforms several alternatives even in the case of external interference and changing network conditions. Further, our experimental evaluation of MuDRA on the ORBIT testbed shows that MuDRA outperforms other schemes and supports high throughput multicast flows to hundreds of nodes while meeting quality requirements. As an example application, MuDRA can support multiple high quality video streams, where 90% of the nodes report excellent or very good video quality. Next, we specifically focus on ensuring high Quality of Experience (QoE) for video streaming over WiFi multicast. We formulate the problem of joint adaptation of multicast transmission rate and video rate for ensuring high video QoE as a utility maximization problem and propose an online control algorithm called DYVR which is based on Lyapunov optimization techniques. We evaluated the performance of DYVR through analysis, simulations, and experiments using a testbed composed of Android devices and o the shelf APs. Our evaluation shows that DYVR can ensure high video rates while guaranteeing a low but acceptable number of segment losses, buffer underflows, and video rate switches. We leverage the lessons learnt from AMuSe for WiFi to address the performance issues with LTE evolved Multimedia Broadcast/Multicast Service (eMBMS). We present the Dynamic Monitoring (DyMo) system which provides low-overhead and real-time feedback about eMBMS performance. DyMo employs eMBMS for broadcasting instructions which indicate the reporting rates as a function of the observed Quality of Service (QoS) for each UE. This simple feedback mechanism collects very limited QoS reports which can be used for network optimization. We evaluated the performance of DyMo analytically and via simulations. DyMo infers the optimal eMBMS settings with extremely low overhead, while meeting strict QoS requirements under different UE mobility patterns and presence of network component failures. In the second part of the thesis, we study datacenter networks which are key enablers of the end-user applications such as video streaming and storage. Datacenter applications such as distributed file systems, one-to-many virtual machine migrations, and large-scale data processing involve bulk multicast flows. We propose a hardware and software system for enabling physical layer optical multicast in datacenter networks using passive optical splitters. We built a prototype and developed a simulation environment to evaluate the performance of the system for bulk multicasting. Our evaluation shows that the optical multicast architecture can achieve higher throughput and lower latency than IP multicast and peer-to-peer multicast schemes with lower switching energy consumption. Finally, we study the problem of congestion control in datacenter networks. Quantized Congestion Control (QCN), a switch-supported standard, utilizes direct multi-bit feedback from the network for hardware rate limiting. Although QCN has been shown to be fast-reacting and effective, being a Layer-2 technology limits its adoption in IP-routed Layer 3 datacenters. We address several design challenges to overcome QCN feedback's Layer- 2 limitation and use it to design window-based congestion control (QCN-CC) and load balancing (QCN-LB) schemes. Our extensive simulations, based on real world workloads, demonstrate the advantages of explicit, multi-bit congestion feedback, especially in a typical environment where intra-datacenter traffic with short Round Trip Times (RTT: tens of s) run in conjunction with web-facing traffic with long RTTs (tens of milliseconds)

Does Clinical Supervision Impact Supervisee Competence in Clinical Practice: A Systematic Review. Student and Supervisor Experiences of the Systemic Practice Scale (SPS): A Discourse Analysis

Clinical supervision is a key factor in the professional development and competence of the supervisee. The recent shift towards competence-based practice has highlighted a need to understand the relationship between supervision and supervisee competence further. A systematic review following PRISMA-P guidelines aimed to summarise and synthesise the literature across five databases exploring the impact of supervision on supervisee competence and the factors that may contribute to effective supervision. Eleven papers met the search criteria and were included within the review. A narrative synthesis of the findings provided some evidence of a positive relationship between supervision and supervisee competence with feedback and the supervisory relationship shown as important factors. The implications for future research and practice are discussed

Network reputation-based quality optimization of video delivery in heterogeneous wireless environments

The mass-market adoption of high-end mobile devices and increasing amount of video traffic has led the mobile operators to adopt various solutions to help them cope with the explosion of mobile broadband data traffic, while ensuring high Quality of Service (QoS) levels to their services. Deploying small-cell base stations within the existing macro-cellular networks and offloading traffic from the large macro-cells to the small cells is seen as a promising solution to increase capacity and improve network performance at low cost. Parallel use of diverse technologies is also employed. The result is a heterogeneous network environment (HetNets), part of the next generation network deployments. In this context, this thesis makes a step forward towards the “Always Best Experience” paradigm, which considers mobile users seamlessly roaming in the HetNets environment. Supporting ubiquitous connectivity and enabling very good quality of rich mobile services anywhere and anytime is highly challenging, mostly due to the heterogeneity of the selection criteria, such as: application requirements (e.g., voice, video, data, etc.); different device types and with various capabilities (e.g., smartphones, netbooks, laptops, etc.); multiple overlapping networks using diverse technologies (e.g., Wireless Local Area Networks (IEEE 802.11), Cellular Networks Long Term Evolution (LTE), etc.) and different user preferences. In fact, the mobile users are facing a complex decision when they need to dynamically select the best value network to connect to in order to get the “Always Best Experience”. This thesis presents three major contributions to solve the problem described above: 1) The Location-based Network Prediction mechanism in heterogeneous wireless networks (LNP) provides a shortlist of best available networks to the mobile user based on his location, history record and routing plan; 2) Reputation-oriented Access Network Selection mechanism (RANS) selects the best reputation network from the available networks for the mobile user based on the best trade-off between QoS, energy consumptions and monetary cost. The network reputation is defined based on previous user-network interaction, and consequent user experience with the network. 3) Network Reputation-based Quality Optimization of Video Delivery in heterogeneous networks (NRQOVD) makes use of a reputation mechanism to enhance the video content quality via multipath delivery or delivery adaptation