NFV Platforms: Taxonomy, Design Choices and Future Challenges

Due to the intrinsically inefficient service provisioning in traditional networks, Network Function Virtualization (NFV) keeps gaining attention from both industry and academia. By replacing the purpose-built, expensive, proprietary network equipment with software network functions consolidated on commodity hardware, NFV envisions a shift towards a more agile and open service provisioning paradigm. During the last few years, a large number of NFV platforms have been implemented in production environments that typically face critical challenges, including the development, deployment, and management of Virtual Network Functions (VNFs). Nonetheless, just like any complex system, such platforms commonly consist of abounding software and hardware components and usually incorporate disparate design choices based on distinct motivations or use cases. This broad collection of convoluted alternatives makes it extremely arduous for network operators to make proper choices. Although numerous efforts have been devoted to investigating different aspects of NFV, none of them specifically focused on NFV platforms or attempted to explore their design space. In this paper, we present a comprehensive survey on the NFV platform design. Our study solely targets existing NFV platform implementations. We begin with a top-down architectural view of the standard reference NFV platform and present our taxonomy of existing NFV platforms based on what features they provide in terms of a typical network function life cycle. Then we thoroughly explore the design space and elaborate on the implementation choices each platform opts for. We also envision future challenges for NFV platform design in the incoming 5G era. We believe that our study gives a detailed guideline for network operators or service providers to choose the most appropriate NFV platform based on their respective requirements. Our work also provides guidelines for implementing new NFV platforms

Orchestrating datacenters and networks to facilitate the telecom cloud

In the Internet of services, information technology (IT) infrastructure providers play a critical role in making the services accessible to end-users. IT infrastructure providers host platforms and services in their datacenters (DCs). The cloud initiative has been accompanied by the introduction of new computing paradigms, such as Infrastructure as a Service (IaaS) and Software as a Service (SaaS), which have dramatically reduced the time and costs required to develop and deploy a service. However, transport networks become crucial to make services accessible to the user and to operate DCs. Transport networks are currently configured with big static fat pipes based on capacity over-provisioning aiming at guaranteeing traffic demand and other parameters committed in Service Level Agreement (SLA) contracts. Notwithstanding, such over-dimensioning adds high operational costs for DC operators and service providers. Therefore, new mechanisms to provide reconfiguration and adaptability of the transport network to reduce the amount of over-provisioned bandwidth are required. Although cloud-ready transport network architecture was introduced to handle the dynamic cloud and network interaction and Elastic Optical Networks (EONs) can facilitate elastic network operations, orchestration between the cloud and the interconnection network is eventually required to coordinate resources in both strata in a coherent manner. In addition, the explosion of Internet Protocol (IP)-based services requiring not only dynamic cloud and network interaction, but also additional service-specific SLA parameters and the expected benefits of Network Functions Virtualization (NFV), open the opportunity to telecom operators to exploit that cloud-ready transport network and their current infrastructure, to efficiently satisfy network requirements from the services. In the telecom cloud, a pay-per-use model can be offered to support services requiring resources from the transport network and its infrastructure. In this thesis, we study connectivity requirements from representative cloud-based services and explore connectivity models, architectures and orchestration schemes to satisfy them aiming at facilitating the telecom cloud. The main objective of this thesis is demonstrating, by means of analytical models and simulation, the viability of orchestrating DCs and networks to facilitate the telecom cloud. To achieve the main goal we first study the connectivity requirements for DC interconnection and services on a number of scenarios that require connectivity from the transport network. Specifically, we focus on studying DC federations, live-TV distribution, and 5G mobile networks. Next, we study different connectivity schemes, algorithms, and architectures aiming at satisfying those connectivity requirements. In particular, we study polling-based models for dynamic inter-DC connectivity and propose a novel notification-based connectivity scheme where inter-DC connectivity can be delegated to the network operator. Additionally, we explore virtual network topology provisioning models to support services that require service-specific SLA parameters on the telecom cloud. Finally, we focus on studying DC and network orchestration to fulfill simultaneously SLA contracts for a set of customers requiring connectivity from the transport network.En la Internet de los servicios, los proveedores de recursos relacionados con tecnologías de la información juegan un papel crítico haciéndolos accesibles a los usuarios como servicios. Dichos proveedores, hospedan plataformas y servicios en centros de datos. La oferta plataformas y servicios en la nube ha introducido nuevos paradigmas de computación tales como ofrecer la infraestructura como servicio, conocido como IaaS de sus siglas en inglés, y el software como servicio, SaaS. La disponibilidad de recursos en la nube, ha contribuido a la reducción de tiempos y costes para desarrollar y desplegar un servicio. Sin embargo, para permitir el acceso de los usuarios a los servicios así como para operar los centros de datos, las redes de transporte resultan imprescindibles. Actualmente, las redes de transporte están configuradas con conexiones estáticas y su capacidad sobredimensionada para garantizar la demanda de tráfico así como los distintos parámetros relacionados con el nivel de servicio acordado. No obstante, debido a que el exceso de capacidad en las conexiones se traduce en un elevado coste tanto para los operadores de los centros de datos como para los proveedores de servicios, son necesarios nuevos mecanismos que permitan adaptar y reconfigurar la red de forma eficiente de acuerdo a las nuevas necesidades de los servicios a los que dan soporte. A pesar de la introducción de arquitecturas que permiten la gestión de redes de transporte y su interacción con los servicios en la nube de forma dinámica, y de la irrupción de las redes ópticas elásticas, la orquestación entre la nube y la red es necesaria para coordinar de forma coherente los recursos en los distintos estratos. Además, la explosión de servicios basados el Protocolo de Internet, IP, que requieren tanto interacción dinámica con la red como parámetros particulares en los niveles de servicio además de los habituales, así como los beneficios que se esperan de la virtualización de funciones de red, representan una oportunidad para los operadores de red para explotar sus recursos y su infraestructura. La nube de operador permite ofrecer recursos del operador de red a los servicios, de forma similar a un sistema basado en pago por uso. En esta Tesis, se estudian requisitos de conectividad de servicios basados en la nube y se exploran modelos de conectividad, arquitecturas y modelos de orquestación que contribuyan a la realización de la nube de operador. El objetivo principal de esta Tesis es demostrar la viabilidad de la orquestación de centros de datos y redes para facilitar la nube de operador, mediante modelos analíticos y simulaciones. Con el fin de cumplir dicho objetivo, primero estudiamos los requisitos de conectividad para la interconexión de centros de datos y servicios en distintos escenarios que requieren conectividad en la red de transporte. En particular, nos centramos en el estudio de escenarios basados en federaciones de centros de datos, distribución de televisión en directo y la evolución de las redes móviles hacia 5G. A continuación, estudiamos distintos modelos de conectividad, algoritmos y arquitecturas para satisfacer los requisitos de conectividad. Estudiamos modelos de conectividad basados en sondeos para la interconexión de centros de datos y proponemos un modelo basado en notificaciones donde la gestión de la conectividad entre centros de datos se delega al operador de red. Estudiamos la provisión de redes virtuales para soportar en la nube de operador servicios que requieren parámetros específicos en los acuerdos de nivel de servicio además de los habituales. Finalmente, nos centramos en el estudio de la orquestación de centros de datos y redes con el objetivo de satisfacer de forma simultánea requisitos para distintos servicios.Postprint (published version

Towards lightweight, low-latency network function virtualisation at the network edge

Communication networks are witnessing a dramatic growth in the number of connected mobile devices, sensors and the Internet of Everything (IoE) equipment, which have been estimated to exceed 50 billion by 2020, generating zettabytes of traffic each year. In addition, networks are stressed to serve the increased capabilities of the mobile devices (e.g., HD cameras) and to fulfil the users' desire for always-on, multimedia-oriented, and low-latency connectivity. To cope with these challenges, service providers are exploiting softwarised, cost-effective, and flexible service provisioning, known as Network Function Virtualisation (NFV). At the same time, future networks are aiming to push services to the edge of the network, to close physical proximity from the users, which has the potential to reduce end-to-end latency, while increasing the flexibility and agility of allocating resources. However, the heavy footprint of today's NFV platforms and their lack of dynamic, latency-optimal orchestration prevents them from being used at the edge of the network. In this thesis, the opportunities of bringing NFV to the network edge are identified. As a concrete solution, the thesis presents Glasgow Network Functions (GNF), a container-based NFV framework that allocates and dynamically orchestrates lightweight virtual network functions (vNFs) at the edge of the network, providing low-latency network services (e.g., security functions or content caches) to users. The thesis presents a powerful formalisation for the latency-optimal placement of edge vNFs and provides an exact solution using Integer Linear Programming, along with a placement scheduler that relies on Optimal Stopping Theory to efficiently re-calculate the placement following roaming users and temporal changes in latency characteristics. The results of this work demonstrate that GNF's real-world vNF examples can be created and hosted on a variety of hosting devices, including VMs from public clouds and low-cost edge devices typically found at the customer's premises. The results also show that GNF can carefully manage the placement of vNFs to provide low-latency guarantees, while minimising the number of vNF migrations required by the operators to keep the placement latency-optimal

Orchestration of distributed ingestion and processing of IoT data for fog platforms

In recent years there has been an extraordinary growth of the Internet of Things (IoT) and its protocols. The increasing diffusion of electronic devices with identification, computing and communication capabilities is laying ground for the emergence of a highly distributed service and networking environment. The above mentioned situation implies that there is an increasing demand for advanced IoT data management and processing platforms. Such platforms require support for multiple protocols at the edge for extended connectivity with the objects, but also need to exhibit uniform internal data organization and advanced data processing capabilities to fulfill the demands of the application and services that consume IoT data. One of the initial approaches to address this demand is the integration between IoT and the Cloud computing paradigm. There are many benefits of integrating IoT with Cloud computing. The IoT generates massive amounts of data, and Cloud computing provides a pathway for that data to travel to its destination. But today’s Cloud computing models do not quite fit for the volume, variety, and velocity of data that the IoT generates. Among the new technologies emerging around the Internet of Things to provide a new whole scenario, the Fog Computing paradigm has become the most relevant. Fog computing was introduced a few years ago in response to challenges posed by many IoT applications, including requirements such as very low latency, real-time operation, large geo-distribution, and mobility. Also this low latency, geo-distributed and mobility environments are covered by the network architecture MEC (Mobile Edge Computing) that provides an IT service environment and Cloud-computing capabilities at the edge of the mobile network, within the Radio Access Network (RAN) and in close proximity to mobile subscribers. Fog computing addresses use cases with requirements far beyond Cloud-only solution capabilities. The interplay between Cloud and Fog computing is crucial for the evolution of the so-called IoT, but the reach and specification of such interplay is an open problem. This thesis aims to find the right techniques and design decisions to build a scalable distributed system for the IoT under the Fog Computing paradigm to ingest and process data. The final goal is to explore the trade-offs and challenges in the design of a solution from Edge to Cloud to address opportunities that current and future technologies will bring in an integrated way. This thesis describes an architectural approach that addresses some of the technical challenges behind the convergence between IoT, Cloud and Fog with special focus on bridging the gap between Cloud and Fog. To that end, new models and techniques are introduced in order to explore solutions for IoT environments. This thesis contributes to the architectural proposals for IoT ingestion and data processing by 1) proposing the characterization of a platform for hosting IoT workloads in the Cloud providing multi-tenant data stream processing capabilities, the interfaces over an advanced data-centric technology, including the building of a state-of-the-art infrastructure to evaluate the performance and to validate the proposed solution. 2) studying an architectural approach following the Fog paradigm that addresses some of the technical challenges found in the first contribution. The idea is to study an extension of the model that addresses some of the central challenges behind the converge of Fog and IoT. 3) Design a distributed and scalable platform to perform IoT operations in a moving data environment. The idea after study data processing in Cloud, and after study the convenience of the Fog paradigm to solve the IoT close to the Edge challenges, is to define the protocols, the interfaces and the data management to solve the ingestion and processing of data in a distributed and orchestrated manner for the Fog Computing paradigm for IoT in a moving data environment.En els últims anys hi ha hagut un gran creixement del Internet of Things (IoT) i els seus protocols. La creixent difusió de dispositius electrònics amb capacitats d'identificació, computació i comunicació esta establint les bases de l’aparició de serveis altament distribuïts i del seu entorn de xarxa. L’esmentada situació implica que hi ha una creixent demanda de plataformes de processament i gestió avançada de dades per IoT. Aquestes plataformes requereixen suport per a múltiples protocols al Edge per connectivitat amb el objectes, però també necessiten d’una organització de dades interna i capacitats avançades de processament de dades per satisfer les demandes de les aplicacions i els serveis que consumeixen dades IoT. Una de les aproximacions inicials per abordar aquesta demanda és la integració entre IoT i el paradigma del Cloud computing. Hi ha molts avantatges d'integrar IoT amb el Cloud. IoT genera quantitats massives de dades i el Cloud proporciona una via perquè aquestes dades viatgin a la seva destinació. Però els models actuals del Cloud no s'ajusten del tot al volum, varietat i velocitat de les dades que genera l'IoT. Entre les noves tecnologies que sorgeixen al voltant del IoT per proporcionar un escenari nou, el paradigma del Fog Computing s'ha convertit en la més rellevant. Fog Computing es va introduir fa uns anys com a resposta als desafiaments que plantegen moltes aplicacions IoT, incloent requisits com baixa latència, operacions en temps real, distribució geogràfica extensa i mobilitat. També aquest entorn està cobert per l'arquitectura de xarxa MEC (Mobile Edge Computing) que proporciona serveis de TI i capacitats Cloud al edge per la xarxa mòbil dins la Radio Access Network (RAN) i a prop dels subscriptors mòbils. El Fog aborda casos d?us amb requisits que van més enllà de les capacitats de solucions només Cloud. La interacció entre Cloud i Fog és crucial per a l'evolució de l'anomenat IoT, però l'abast i especificació d'aquesta interacció és un problema obert. Aquesta tesi té com objectiu trobar les decisions de disseny i les tècniques adequades per construir un sistema distribuït escalable per IoT sota el paradigma del Fog Computing per a ingerir i processar dades. L'objectiu final és explorar els avantatges/desavantatges i els desafiaments en el disseny d'una solució des del Edge al Cloud per abordar les oportunitats que les tecnologies actuals i futures portaran d'una manera integrada. Aquesta tesi descriu un enfocament arquitectònic que aborda alguns dels reptes tècnics que hi ha darrere de la convergència entre IoT, Cloud i Fog amb especial atenció a reduir la bretxa entre el Cloud i el Fog. Amb aquesta finalitat, s'introdueixen nous models i tècniques per explorar solucions per entorns IoT. Aquesta tesi contribueix a les propostes arquitectòniques per a la ingesta i el processament de dades IoT mitjançant 1) proposant la caracterització d'una plataforma per a l'allotjament de workloads IoT en el Cloud que proporcioni capacitats de processament de flux de dades multi-tenant, les interfícies a través d'una tecnologia centrada en dades incloent la construcció d'una infraestructura avançada per avaluar el rendiment i validar la solució proposada. 2) estudiar un enfocament arquitectònic seguint el paradigma Fog que aborda alguns dels reptes tècnics que es troben en la primera contribució. La idea és estudiar una extensió del model que abordi alguns dels reptes centrals que hi ha darrere de la convergència de Fog i IoT. 3) Dissenyar una plataforma distribuïda i escalable per a realitzar operacions IoT en un entorn de dades en moviment. La idea després d'estudiar el processament de dades a Cloud, i després d'estudiar la conveniència del paradigma Fog per resoldre el IoT prop dels desafiaments Edge, és definir els protocols, les interfícies i la gestió de dades per resoldre la ingestió i processament de dades en un distribuït i orquestrat per al paradigma Fog Computing per a l'IoT en un entorn de dades en moviment

5G Multi-access Edge Computing: Security, Dependability, and Performance

The main innovation of the Fifth Generation (5G) of mobile networks is the ability to provide novel services with new and stricter requirements. One of the technologies that enable the new 5G services is the Multi-access Edge Computing (MEC). MEC is a system composed of multiple devices with computing and storage capabilities that are deployed at the edge of the network, i.e., close to the end users. MEC reduces latency and enables contextual information and real-time awareness of the local environment. MEC also allows cloud offloading and the reduction of traffic congestion. Performance is not the only requirement that the new 5G services have. New mission-critical applications also require high security and dependability. These three aspects (security, dependability, and performance) are rarely addressed together. This survey fills this gap and presents 5G MEC by addressing all these three aspects. First, we overview the background knowledge on MEC by referring to the current standardization efforts. Second, we individually present each aspect by introducing the related taxonomy (important for the not expert on the aspect), the state of the art, and the challenges on 5G MEC. Finally, we discuss the challenges of jointly addressing the three aspects.Comment: 33 pages, 11 figures, 15 tables. This paper is under review at IEEE Communications Surveys & Tutorials. Copyright IEEE 202

View on 5G Architecture: Version 1.0

The current white paper focuses on the produced results after one year research mainly from 16 projects working on the abovementioned domains. During several months, representatives from these projects have worked together to identify the key findings of their projects and capture the commonalities and also the different approaches and trends. Also they have worked to determine the challenges that remain to be overcome so as to meet the 5G requirements. The goal of 5G Architecture Working Group is to use the results captured in this white paper to assist the participating projects achieve a common reference framework. The work of this working group will continue during the following year so as to capture the latest results to be produced by the projects and further elaborate this reference framework. The 5G networks will be built around people and things and will natively meet the requirements of three groups of use cases: • Massive broadband (xMBB) that delivers gigabytes of bandwidth on demand • Massive machine-type communication (mMTC) that connects billions of sensors and machines • Critical machine-type communication (uMTC) that allows immediate feedback with high reliability and enables for example remote control over robots and autonomous driving. The demand for mobile broadband will continue to increase in the next years, largely driven by the need to deliver ultra-high definition video. However, 5G networks will also be the platform enabling growth in many industries, ranging from the IT industry to the automotive, manufacturing industries entertainment, etc. 5G will enable new applications like for example autonomous driving, remote control of robots and tactile applications, but these also bring a lot of challenges to the network. Some of these are related to provide low latency in the order of few milliseconds and high reliability compared to fixed lines. But the biggest challenge for 5G networks will be that the services to cater for a diverse set of services and their requirements. To achieve this, the goal for 5G networks will be to improve the flexibility in the architecture. The white paper is organized as follows. In section 2 we discuss the key business and technical requirements that drive the evolution of 4G networks into the 5G. In section 3 we provide the key points of the overall 5G architecture where as in section 4 we elaborate on the functional architecture. Different issues related to the physical deployment in the access, metro and core networks of the 5G network are discussed in section 5 while in section 6 we present software network enablers that are expected to play a significant role in the future networks. Section 7 presents potential impacts on standardization and section 8 concludes the white paper

A manifesto for future generation cloud computing: research directions for the next decade

The Cloud computing paradigm has revolutionised the computer science horizon during the past decade and has enabled the emergence of computing as the fifth utility. It has captured significant attention of academia, industries, and government bodies. Now, it has emerged as the backbone of modern economy by offering subscription-based services anytime, anywhere following a pay-as-you-go model. This has instigated (1) shorter establishment times for start-ups, (2) creation of scalable global enterprise applications, (3) better cost-to-value associativity for scientific and high performance computing applications, and (4) different invocation/execution models for pervasive and ubiquitous applications. The recent technological developments and paradigms such as serverless computing, software-defined networking, Internet of Things, and processing at network edge are creating new opportunities for Cloud computing. However, they are also posing several new challenges and creating the need for new approaches and research strategies, as well as the re-evaluation of the models that were developed to address issues such as scalability, elasticity, reliability, security, sustainability, and application models. The proposed manifesto addresses them by identifying the major open challenges in Cloud computing, emerging trends, and impact areas. It then offers research directions for the next decade, thus helping in the realisation of Future Generation Cloud Computing