1,549 research outputs found
Network slicing via function decomposition and flexible network design
Proceeding of: IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PMRC 2017)We argue for flexible network design as an architecture prototype for next generation networks. Such flexible design is developed by capitalizing on the concept of network function decomposition in conjunction with with its relation to network slicing. A detailed view of the proposed functional architecture is put forward, where the role of network function blocks for forming network slices with given requirements is underlined. We further highlight the impact of common architecture over multiple tenants and elaborate on the emerging multi-tenancy business models along with the resulting implications on security.This work has been performed in the framework of the H2020-ICT-2014-2 project 5G NORMA
Design, implementation and experimental evaluation of a network-slicing aware mobile protocol stack
Mención Internacional en el título de doctorWith 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.This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Francisco Valera Pintor.- Secretario: Vincenzo Sciancalepore.- Vocal: Xenofon Fouka
Enabling the orchestration of IoT slices through edge and cloud microservice platforms
This article addresses one of the main challenges related to the practical deployment of Internet of Things (IoT) solutions: the coordinated operation of entities at different infrastructures to support the automated orchestration of end-to-end Internet of Things services. This idea is referred to as "Internet of Things slicing" and is based on the network slicing concept already defined for the Fifth Generation (5G) of mobile networks. In this context, we present the architectural design of a slice orchestrator addressing the aforementioned challenge, based on well-known standard technologies and protocols. The proposed solution is able to integrate existing technologies, like cloud computing, with other more recent technologies like edge computing and network slicing. In addition, a functional prototype of the proposed orchestrator has been implemented, using open-source software and microservice platforms. As a first step to prove the practical feasibility of our solution, the implementation of the orchestrator considers cloud and edge domains. The validation results obtained from the prototype prove the feasibility of the solution from a functional perspective, verifying its capacity to deploy Internet of Things related functions even on resource constrained platforms. This approach enables new application models where these Internet of Things related functions can be onboarded on small unmanned aerial vehicles, offering a flexible and cost-effective solution to deploy these functions at the network edge. In addition, this proposal can also be used on commercial cloud platforms, like the Google Compute Engine, showing that it can take advantage of the benefits of edge and cloud computing respectivelyThe work of Ivan Vidal and Francisco Valera was partially supported by the European H2020 5GinFIRE project (grant agreement 732497), and by the 5GCity project (TEC2016-76795-C6-3-R) funded by the Spanish Ministry of Economy and Competitiveness
Iris: Deep Reinforcement Learning Driven Shared Spectrum Access Architecture for Indoor Neutral-Host Small Cells
We consider indoor mobile access, a vital use case for current and future
mobile networks. For this key use case, we outline a vision that combines a
neutral-host based shared small-cell infrastructure with a common pool of
spectrum for dynamic sharing as a way forward to proliferate indoor small-cell
deployments and open up the mobile operator ecosystem. Towards this vision, we
focus on the challenges pertaining to managing access to shared spectrum (e.g.,
3.5GHz US CBRS spectrum). We propose Iris, a practical shared spectrum access
architecture for indoor neutral-host small-cells. At the core of Iris is a deep
reinforcement learning based dynamic pricing mechanism that efficiently
mediates access to shared spectrum for diverse operators in a way that provides
incentives for operators and the neutral-host alike. We then present the Iris
system architecture that embeds this dynamic pricing mechanism alongside
cloud-RAN and RAN slicing design principles in a practical neutral-host design
tailored for the indoor small-cell environment. Using a prototype
implementation of the Iris system, we present extensive experimental evaluation
results that not only offer insight into the Iris dynamic pricing process and
its superiority over alternative approaches but also demonstrate its deployment
feasibility
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