152 research outputs found
Resource Orchestration in Softwarized Networks
Network softwarization is an emerging research area that is envisioned to revolutionize the way network infrastructure is designed, operated, and managed today. Contemporary telecommunication networks are going through a major transformation, and softwarization is recognized as a crucial enabler of this transformation by both academia and industry. Softwarization promises to overcome the current ossified state of Internet network architecture and evolve towards a more open, agile, flexible, and programmable networking paradigm that will reduce both capital and operational expenditures, cut-down time-to-market of new services, and create new revenue streams. Software-Defined Networking (SDN) and Network Function Virtualization (NFV) are two complementary networking technologies that have established themselves as the cornerstones of network softwarization. SDN decouples the control and data planes to provide enhanced programmability and faster innovation of networking technologies. It facilitates simplified network control, scalability, availability, flexibility, security, cost-reduction, autonomic management, and fine-grained control of network traffic. NFV utilizes virtualization technology to reduce dependency on underlying hardware by moving packet processing activities from proprietary hardware middleboxes to virtualized entities that can run on commodity hardware. Together SDN and NFV simplify network infrastructure by utilizing standardized and commodity hardware for both compute and networking; bringing the benefits of agility, economies of scale, and flexibility of data centers to networks.
Network softwarization provides the tools required to re-architect the current network infrastructure of the Internet. However, the effective application of these tools requires efficient utilization of networking resources in the softwarized environment. Innovative techniques and mechanisms are required for all aspects of network management and control. The overarching goal of this thesis is to address several key resource orchestration challenges in softwarized networks. The resource allocation and orchestration techniques presented in this thesis utilize the functionality provided by softwarization to reduce operational cost, improve resource utilization, ensure scalability, dynamically scale resource pools according to demand, and optimize energy utilization
Online Service Provisioning in NFV-enabled Networks Using Deep Reinforcement Learning
In this paper, we study a Deep Reinforcement Learning (DRL) based framework
for an online end-user service provisioning in a Network Function
Virtualization (NFV)-enabled network. We formulate an optimization problem
aiming to minimize the cost of network resource utilization. The main challenge
is provisioning the online service requests by fulfilling their Quality of
Service (QoS) under limited resource availability. Moreover, fulfilling the
stochastic service requests in a large network is another challenge that is
evaluated in this paper. To solve the formulated optimization problem in an
efficient and intelligent manner, we propose a Deep Q-Network for Adaptive
Resource allocation (DQN-AR) in NFV-enable network for function placement and
dynamic routing which considers the available network resources as DQN states.
Moreover, the service's characteristics, including the service life time and
number of the arrival requests, are modeled by the Uniform and Exponential
distribution, respectively. In addition, we evaluate the computational
complexity of the proposed method. Numerical results carried out for different
ranges of parameters reveal the effectiveness of our framework. In specific,
the obtained results show that the average number of admitted requests of the
network increases by 7 up to 14% and the network utilization cost decreases by
5 and 20 %
Algorithms for advance bandwidth reservation in media production networks
Media production generally requires many geographically distributed actors (e.g., production houses, broadcasters, advertisers) to exchange huge amounts of raw video and audio data. Traditional distribution techniques, such as dedicated point-to-point optical links, are highly inefficient in terms of installation time and cost. To improve efficiency, shared media production networks that connect all involved actors over a large geographical area, are currently being deployed. The traffic in such networks is often predictable, as the timing and bandwidth requirements of data transfers are generally known hours or even days in advance. As such, the use of advance bandwidth reservation (AR) can greatly increase resource utilization and cost efficiency. In this paper, we propose an Integer Linear Programming formulation of the bandwidth scheduling problem, which takes into account the specific characteristics of media production networks, is presented. Two novel optimization algorithms based on this model are thoroughly evaluated and compared by means of in-depth simulation results
Traffic and Resource Management in Robust Cloud Data Center Networks
Cloud Computing is becoming the mainstream paradigm, as organizations, both large and small, begin to harness its benefits. Cloud computing gained its success for giving IT exactly what it needed: The ability to grow and shrink computing resources, on the go, in a cost-effective manner, without the anguish of infrastructure design and setup. The ability to adapt computing demands to market fluctuations is just one of the many benefits that cloud computing has to offer, this is why this new paradigm is rising rapidly. According to a Gartner report, the total sales of the various cloud services will be worth 204 billion dollars worldwide in 2016. With this massive growth, the performance of the underlying infrastructure is crucial to its success and sustainability. Currently, cloud computing heavily depends on data centers for its daily business needs. In fact, it is through the virtualization of data centers that the concept of "computing as a utility" emerged. However, data center virtualization is still in its infancy; and there exists a plethora of open research issues and challenges related to data center virtualization, including but not limited to, optimized topologies and protocols, embedding design methods and online algorithms, resource provisioning and allocation, data center energy efficiency, fault tolerance issues and fault tolerant design, improving service availability under failure conditions, enabling network programmability, etc.
This dissertation will attempt to elaborate and address key research challenges and problems related to the design and operation of efficient virtualized data centers and data center infrastructure for cloud services. In particular, we investigate the problem of scalable traffic management and traffic engineering methods in data center networks and present a decomposition method to exactly solve the problem with considerable runtime improvement over mathematical-based formulations. To maximize the network's admissibility and increase its revenue, cloud providers must make efficient use of their's network resources. This goal is highly correlated with the employed resource allocation/placement schemes; formally known as the virtual network embedding problem. This thesis looks at multi-facets of this latter problem; in particular, we study the embedding problem for services with one-to-many communication mode; or what we denote as the multicast virtual network embedding problem. Then, we tackle the survivable virtual network embedding problem by proposing a fault-tolerance design that provides guaranteed service continuity in the event of server failure. Furthermore, we consider the embedding problem for elastic services in the event of heterogeneous node failures. Finally, in the effort to enable and support data center network programmability, we study the placement problem of softwarized network functions (e.g., load balancers, firewalls, etc.), formally known as the virtual network function assignment problem. Owing to its combinatorial complexity, we propose a novel decomposition method, and we numerically show that it is hundred times faster than mathematical formulations from recent existing literature
Server resource dimensioning and routing of service function chain in NFV network architectures
The Network Function Virtualization (NFV) technology aims at virtualizing the network service with the execution of the single service components in Virtual Machines activated on Commercial-off-the-shelf (COTS) servers. Any service is represented by the Service Function Chain (SFC) that is a set of VNFs to be executed according to a given order. The running of VNFs needs the instantiation of VNF instances (VNFI) that in general are software components executed on Virtual Machines. In this paper we cope with the routing and resource dimensioning problem in NFV architectures. We formulate the optimization problem and due to its NP-hard complexity, heuristics are proposed for both cases of offline and online traffic demand. We show how the heuristics works correctly by guaranteeing a uniform occupancy of the server processing capacity and the network link bandwidth. A consolidation algorithm for the power consumption minimization is also proposed. The application of the consolidation algorithm allows for a high power consumption saving that however is to be paid with an increase in SFC blocking probability
Doctor of Philosophy
dissertationNetwork emulation has become an indispensable tool for the conduct of research in networking and distributed systems. It offers more realism than simulation and more control and repeatability than experimentation on a live network. However, emulation testbeds face a number of challenges, most prominently realism and scale. Because emulation allows the creation of arbitrary networks exhibiting a wide range of conditions, there is no guarantee that emulated topologies reflect real networks; the burden of selecting parameters to create a realistic environment is on the experimenter. While there are a number of techniques for measuring the end-to-end properties of real networks, directly importing such properties into an emulation has been a challenge. Similarly, while there exist numerous models for creating realistic network topologies, the lack of addresses on these generated topologies has been a barrier to using them in emulators. Once an experimenter obtains a suitable topology, that topology must be mapped onto the physical resources of the testbed so that it can be instantiated. A number of restrictions make this an interesting problem: testbeds typically have heterogeneous hardware, scarce resources which must be conserved, and bottlenecks that must not be overused. User requests for particular types of nodes or links must also be met. In light of these constraints, the network testbed mapping problem is NP-hard. Though the complexity of the problem increases rapidly with the size of the experimenter's topology and the size of the physical network, the runtime of the mapper must not; long mapping times can hinder the usability of the testbed. This dissertation makes three contributions towards improving realism and scale in emulation testbeds. First, it meets the need for realistic network conditions by creating Flexlab, a hybrid environment that couples an emulation testbed with a live-network testbed, inheriting strengths from each. Second, it attends to the need for realistic topologies by presenting a set of algorithms for automatically annotating generated topologies with realistic IP addresses. Third, it presents a mapper, assign, that is capable of assigning experimenters' requested topologies to testbeds' physical resources in a manner that scales well enough to handle large environments
NFV orchestration in edge and fog scenarios
Mención Internacional en el título de doctorLas infraestructuras de red actuales soportan una
variedad diversa de servicios como video bajo demanda,
video conferencias, redes sociales, sistemas
de educación, o servicios de almacenamiento de
fotografías. Gran parte de la población mundial ha
comenzado a utilizar estos servicios, y los utilizan
diariamente. Proveedores de Cloud y operadores
de infraestructuras de red albergan el tráfico de
red generado por estos servicios, y sus tareas de
gestión no solo implican realizar el enrutamiento
del tráfico, sino también el procesado del tráfico de
servicios de red. Tradicionalmente, el procesado
del tráfico ha sido realizado mediante aplicaciones/
programas desplegados en servidores que estaban
dedicados en exclusiva a tareas concretas
como la inspección de paquetes. Sin embargo, en
los últimos anos los servicios de red se han virtualizado
y esto ha dado lugar al paradigma de
virtualización de funciones de red (Network Function
Virtualization (NFV) siguiendo las siglas en
ingles), en el que las funciones de red de un servicio
se ejecutan en contenedores o máquinas virtuales
desacopladas de la infraestructura hardware. Como
resultado, el procesado de tráfico se ha ido
haciendo más flexible gracias al laxo acople del
software y hardware, y a la posibilidad de compartir
funciones de red típicas, como firewalls, entre
los distintos servicios de red.
NFV facilita la automatización de operaciones
de red, ya que tareas como el escalado, o la migración
son típicamente llevadas a cabo mediante
un conjunto de comandos previamente definidos
por la tecnología de virtualización pertinente, bien
mediante contenedores o máquinas virtuales. De
todos modos, sigue siendo necesario decidir el en rutamiento y procesado del tráfico de cada servicio
de red. En otras palabras, que servidores tienen
que encargarse del procesado del tráfico, y que
enlaces de la red tienen que utilizarse para que las
peticiones de los usuarios lleguen a los servidores
finales, es decir, el conocido como embedding problem.
Bajo el paraguas del paradigma NFV, a este
problema se le conoce en inglés como Virtual Network
Embedding (VNE), y esta tesis utiliza el termino
“NFV orchestration algorithm” para referirse
a los algoritmos que resuelven este problema. El
problema del VNE es NP-hard, lo cual significa
que que es imposible encontrar una solución optima
en un tiempo polinómico, independientemente
del tamaño de la red. Como consecuencia, la comunidad
investigadora y de telecomunicaciones
utilizan heurísticos que encuentran soluciones de
manera más rápida que productos para la resolución
de problemas de optimización.
Tradicionalmente, los “NFV orchestration algorithms”
han intentado minimizar los costes de
despliegue derivados de las soluciones asociadas.
Por ejemplo, estos algoritmos intentan no consumir
el ancho de banda de la red, y usar rutas cortas
para no utilizar tantos recursos. Además, una tendencia
reciente ha llevado a la comunidad investigadora
a utilizar algoritmos que minimizan el
consumo energético de los servicios desplegados,
bien mediante la elección de dispositivos con un
consumo energético más eficiente, o mediante el
apagado de dispositivos de red en desuso. Típicamente,
las restricciones de los problemas de VNE se
han resumido en un conjunto de restricciones asociadas
al uso de recursos y consumo energético, y las
soluciones se diferenciaban por la función objetivo
utilizada. Pero eso era antes de la 5a generación de
redes móviles (5G) se considerase en el problema
de VNE. Con la aparición del 5G, nuevos servicios
de red y casos de uso entraron en escena. Los estándares
hablaban de comunicaciones ultra rápidas
y fiables (Ultra-Reliable and Low Latency Communications
(URLLC) usando las siglas en inglés) con
latencias por debajo de unos pocos milisegundos y
fiabilidades del 99.999%, una banda ancha mejorada
(enhanced Mobile Broadband (eMBB) usando
las siglas en inglés) con notorios incrementos en
el flujo de datos, e incluso la consideración de comunicaciones
masivas entre maquinas (Massive
Machine-Type Communications (mMTC) usando
las siglas en inglés) entre dispositivos IoT. Es más,
paradigmas como edge y fog computing se incorporaron a la tecnología 5G, e introducían la idea
de tener dispositivos de computo más cercanos al
usuario final. Como resultado, el problema del VNE
tenía que incorporar los nuevos requisitos como
restricciones a tener en cuenta, y toda solución
debía satisfacer bajas latencias, alta fiabilidad, y
mayores tasas de transmisión.
Esta tesis estudia el problema des VNE, y propone
algunos heurísticos que lidian con las restricciones
asociadas a servicios 5G en escenarios
edge y fog, es decir, las soluciones propuestas se
encargan de asignar funciones virtuales de red a
servidores, y deciden el enrutamiento del trafico
en las infraestructuras 5G con dispositivos edge y
fog. Para evaluar el rendimiento de las soluciones
propuestas, esta tesis estudia en primer lugar la
generación de grafos que representan redes 5G.
Los mecanismos propuestos para la generación de
grafos sirven para representar distintos escenarios
5G. En particular, escenarios de federación en
los que varios dominios comparten recursos entre
ellos. Los grafos generados también representan
servidores en el edge, así como dispositivos fog con
una batería limitada. Además, estos grafos tienen
en cuenta los requisitos de estándares, y la demanda
que se espera en las redes 5G. La generación de
grafos propuesta sirve para representar escenarios
federación en los que varios dominios comparten
recursos entre ellos, y redes 5G con servidores edge,
así como dispositivos fog estáticos o móviles con
una batería limitada. Los grafos generados para
infraestructuras 5G tienen en cuenta los requisitos
de estándares, y la demanda de red que se espera
en las redes 5G. Además, los grafos son diferentes
en función de la densidad de población, y el área
de estudio, es decir, si es una zona industrial, una
autopista, o una zona urbana.
Tras detallar la generación de grafos que representan
redes 5G, esta tesis propone algoritmos de
orquestación NFV para resolver con el problema
del VNE. Primero, se centra en escenarios federados
en los que los servicios de red se tienen que
asignar no solo a la infraestructura de un dominio,
sino a los recursos compartidos en la federación
de dominios. Dos problemas diferentes han sido estudiados,
uno es el problema del VNE propiamente
dicho sobre una infraestructura federada, y el otro
es la delegación de servicios de red. Es decir, si
un servicio de red se debe desplegar localmente
en un dominio, o en los recursos compartidos por
la federación de dominios; a sabiendas de que el último caso supone el pago de cuotas por parte del
dominio local a cambio del despliegue del servicio
de red. En segundo lugar, esta tesis propone
OKpi, un algoritmo de orquestación NFV para conseguir
la calidad de servicio de las distintas slices
de las redes 5G. Conceptualmente, el slicing consiste
en partir la red de modo que cada servicio
de red sea tratado de modo diferente dependiendo
del trozo al que pertenezca. Por ejemplo, una
slice de eHealth reservara los recursos de red necesarios
para conseguir bajas latencias en servicios
como operaciones quirúrgicas realizadas de manera
remota. Cada trozo (slice) está destinado a
unos servicios específicos con unos requisitos muy
concretos, como alta fiabilidad, restricciones de
localización, o latencias de un milisegundo. OKpi
es un algoritmo de orquestación NFV que consigue
satisfacer los requisitos de servicios de red en los
distintos trozos, o slices de la red. Tras presentar
OKpi, la tesis resuelve el problema del VNE en redes
5G con dispositivos fog estáticos y móviles. El
algoritmo de orquestación NFV presentado tiene
en cuenta las limitaciones de recursos de computo
de los dispositivos fog, además de los problemas
de falta de cobertura derivados de la movilidad de
los dispositivos.
Para concluir, esta tesis estudia el escalado
de servicios vehiculares Vehicle-to-Network (V2N),
que requieren de bajas latencias para servicios como
la prevención de choques, avisos de posibles
riesgos, y conducción remota. Para estos servicios,
los atascos y congestiones en la carretera pueden
causar el incumplimiento de los requisitos de latencia.
Por tanto, es necesario anticiparse a esas
circunstancias usando técnicas de series temporales
que permiten saber el tráfico inminente en los
siguientes minutos u horas, para así poder escalar
el servicio V2N adecuadamente.Current network infrastructures handle a diverse
range of network services such as video
on demand services, video-conferences, social
networks, educational systems, or photo
storage services. These services have been
embraced by a significant amount of the
world population, and are used on a daily basis.
Cloud providers and Network operators’
infrastructures accommodate the traffic rates
that the aforementioned services generate, and
their management tasks do not only involve
the traffic steering, but also the processing of
the network services’ traffic. Traditionally,
the traffic processing has been assessed via
applications/programs deployed on servers
that were exclusively dedicated to a specific
task as packet inspection. However, in recent
years network services have stated to be
virtualized and this has led to the Network
Function Virtualization (Network Function
Virtualization (NFV)) paradigm, in which the
network functions of a service run on containers
or virtual machines that are decoupled
from the hardware infrastructure. As a result,
the traffic processing has become more flexible
because of the loose coupling between
software and hardware, and the possibility
of sharing common network functions, as
firewalls, across multiple network services.
NFV eases the automation of network operations,
since scaling and migrations tasks
are typically performed by a set of commands
predefined by the virtualization technology,
either containers or virtual machines. However,
it is still necessary to decide the traffic steering and processing of every network
service. In other words, which servers will
hold the traffic processing, and which are the
network links to be traversed so the users’ requests
reach the final servers, i.e., the network
embedding problem. Under the umbrella of
NFV, this problem is known as Virtual Network
Embedding (VNE), and this thesis refers
as “NFV orchestration algorithms” to those
algorithms solving such a problem. The VNE
problem is a NP-hard, meaning that it is impossible
to find optimal solutions in polynomial
time, no matter the network size. As a
consequence, the research and telecommunications
community rely on heuristics that find
solutions quicker than a commodity optimization
solver.
Traditionally, NFV orchestration algorithms
have tried to minimize the deployment
costs derived from their solutions. For example,
they try to not exhaust the network
bandwidth, and use short paths to use less
network resources. Additionally, a recent
tendency led the research community towards
algorithms that minimize the energy consumption
of the deployed services, either
by selecting more energy efficient devices
or by turning off those network devices that
remained unused. VNE problem constraints
were typically summarized in a set of resources/energy constraints, and the solutions
differed on which objectives functions were
aimed for. But that was before 5th generation
of mobile networks (5G) were considered
in the VNE problem. With the appearance
of 5G, new network services and use cases
started to emerge. The standards talked about
Ultra Reliable Low Latency Communication
(Ultra-Reliable and Low Latency Communications
(URLLC)) with latencies below few
milliseconds and 99.999% reliability, an enhanced
mobile broadband (enhanced Mobile
Broadband (eMBB)) with significant data
rate increases, and even the consideration
of massive machine-type communications
(Massive Machine-Type Communications
(mMTC)) among Internet of Things (IoT) devices.
Moreover, paradigms such as edge and
fog computing blended with the 5G technology
to introduce the idea of having computing
devices closer to the end users. As a result, the VNE problem had to incorporate the new
requirements as constraints to be taken into
account, and every solution should either
satisfy low latencies, high reliability, or larger
data rates.
This thesis studies the VNE problem, and
proposes some heuristics tackling the constraints
related to 5G services in Edge and
fog scenarios, that is, the proposed solutions
assess the assignment of Virtual Network
Functions to resources, and the traffic steering
across 5G infrastructures that have Edge and
Fog devices. To evaluate the performance
of the proposed solutions, the thesis studies
first the generation of graphs that represent
5G networks. The proposed mechanisms to
generate graphs serve to represent diverse 5G
scenarios. In particular federation scenarios
in which several domains share resources
among themselves. The generated graphs
also represent edge servers, so as fog devices
with limited battery capacity. Additionally,
these graphs take into account the standard
requirements, and the expected demand for
5G networks. Moreover, the graphs differ depending
on the density of population, and the
area of study, i.e., whether it is an industrial
area, a highway, or an urban area.
After detailing the generation of graphs
representing the 5G networks, this thesis proposes
several NFV orchestration algorithms
to tackle the VNE problem. First, it focuses
on federation scenarios in which network services
should be assigned not only to a single
domain infrastructure, but also to the shared
resources of the federation of domains. Two
different problems are studied, one being the
VNE itself over a federated infrastructure, and
the other the delegation of network services.
That is, whether a network service should be
deployed in a local domain, or in the pool
of resources of the federation domain; knowing
that the latter charges the local domain
for hosting the network service. Second, the
thesis proposes OKpi, a NFV orchestration
algorithm to meet 5G network slices quality
of service. Conceptually, network slicing consists
in splitting the network so network services
are treated differently based on the slice
they belong to. For example, an eHealth network
slice will allocate the network resources necessary to meet low latencies for network
services such as remote surgery. Each network
slice is devoted to specific services with
very concrete requirements, as high reliability,
location constraints, or 1ms latencies. OKpi is
a NFV orchestration algorithm that meets the
network service requirements among different
slices. It is based on a multi-constrained
shortest path heuristic, and its solutions satisfy
latency, reliability, and location constraints.
After presenting OKpi, the thesis tackles the
VNE problem in 5G networks with static/moving
fog devices. The presented NFV orchestration
algorithm takes into account the limited
computing resources of fog devices, as well
as the out-of-coverage problems derived from
the devices’ mobility.
To conclude, this thesis studies the scaling
of Vehicle-to-Network (V2N) services, which
require low latencies for network services as
collision avoidance, hazard warning, and remote
driving. For these services, the presence
of traffic jams, or high vehicular traffic congestion
lead to the violation of latency requirements.
Hence, it is necessary to anticipate to
such circumstances by using time-series techniques
that allow to derive the incoming vehicular
traffic flow in the next minutes or hours,
so as to scale the V2N service accordingly.The 5G Exchange (5GEx) project (2015-2018) was an EU-funded project (H2020-ICT-2014-2 grant agreement 671636).
The 5G-TRANSFORMER project (2017-2019) is an EU-funded project (H2020-ICT-2016-2 grant agreement 761536).
The 5G-CORAL project (2017-2019) is an EU-Taiwan project (H2020-ICT-2016-2 grant agreement 761586).Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Ioannis Stavrakakis.- Secretario: Pablo Serrano Yáñez-Mingot.- Vocal: Paul Horatiu Patra
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