Derechos:
Atribución-NoComercial-SinDerivadas 3.0 España
Resumen:
With the arrival of new generation mobile networks, we currently observe a paradigm
shift, where monolithic network functions running on dedicated hardware are now
implemented as software pieces that can be virtualized on general purpose hardware
platforms.With the arrival of new generation mobile networks, we currently observe a paradigm
shift, where monolithic network functions running on dedicated hardware are now
implemented as software pieces that can be virtualized on general purpose hardware
platforms. This paradigm shift stands on the softwarization of network functions and
the adoption of virtualization techniques. Network Function Virtualization (NFV)
comprises softwarization of network elements and virtualization of these components.
It brings multiple advantages: (i) Flexibility, allowing an easy management of the virtual
network functions (VNFs) (deploy, start, stop or update); (ii) efficiency, resources can be
adequately consumed due to the increased flexibility of the network infrastructure; and
(iii) reduced costs, due to the ability of sharing hardware resources. To this end, multiple
challenges must be addressed to effectively leverage of all these benefits.
Network Function Virtualization envisioned the concept of virtual network, resulting in
a key enabler of 5G networks flexibility, Network Slicing. This new paradigm represents
a new way to operate mobile networks where the underlying infrastructure is "sliced"
into logically separated networks that can be customized to the specific needs of the
tenant. This approach also enables the ability of instantiate VNFs at different locations
of the infrastructure, choosing their optimal placement based on parameters such as the
requirements of the service traversing the slice or the available resources. This decision
process is called orchestration and involves all the VNFs withing the same network slice.
The orchestrator is the entity in charge of managing network slices. Hands-on experiments
on network slicing are essential to understand its benefits and limits, and to validate the
design and deployment choices. While some network slicing prototypes have been built
for Radio Access Networks (RANs), leveraging on the wide availability of radio hardware
and open-source software, there is no currently open-source suite for end-to-end network
slicing available to the research community. Similarly, orchestration mechanisms must
be evaluated as well to properly validate theoretical solutions addressing diverse aspects
such as resource assignment or service composition.
This thesis contributes on the study of the mobile networks evolution regarding its
softwarization and cloudification. We identify software patterns for network function
virtualization, including the definition of a novel mobile architecture that squeezes the virtualization architecture by splitting functionality in atomic functions.
Then, we effectively design, implement and evaluate of an open-source network
slicing implementation. Our results show a per-slice customization without paying the
price in terms of performance, also providing a slicing implementation to the research
community. Moreover, we propose a framework to flexibly re-orchestrate a virtualized
network, allowing on-the-fly re-orchestration without disrupting ongoing services. This
framework can greatly improve performance under changing conditions. We evaluate
the resulting performance in a realistic network slicing setup, showing the feasibility and
advantages of flexible re-orchestration.
Lastly and following the required re-design of network functions envisioned during
the study of the evolution of mobile networks, we present a novel pipeline architecture
specifically engineered for 4G/5G Physical Layers virtualized over clouds. The proposed
design follows two objectives, resiliency upon unpredictable computing and parallelization
to increase efficiency in multi-core clouds. To this end, we employ techniques such as tight
deadline control, jitter-absorbing buffers, predictive Hybrid Automatic Repeat Request,
and congestion control. Our experimental results show that our cloud-native approach
attains > 95% of the theoretical spectrum efficiency in hostile environments where stateof-
the-art architectures collapse.[+][-]