Publication: Mechanisms for integration of MEC and NFV for 5G networks in dynamic and heterogeneous scenarios
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2022-06
Defense date
2022-09-21
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Abstract
The 5G technology presents a significant leap into making the Information and Communication
technology and integral part of the industries, and societies. Enhanced connectivity
features unlock a range of different applications that provide unique user experience
such as virtual and augmented reality, or mission-critical communications that
improve the healthcare and environmental protection, digital twin for optimizing the production
lines, etc. Besides the new radio technology, the virtualization technology is
the major enabler of most of the exciting novel applications. Viritualization enables service
providers to customize and shape the existing computing, networking and storage
infrastructure to accommodate the requirements of the different range of customers often
referred as vertical industries.
The Network Function Virtualization (NFV) with the Software-defined Networking
(SDN) are the key technologies that enable deployment of multiple isolated and customized
networks on top of a single administrative domain infrastructure. The Multiaccess
Edge technology revamps carrier’s infrastructure with application-oriented capabilities
feeding applications with context information to elevate the user experience. Even
though initially projected as a mobile operator technology, it is applicable to any service
provider.
This thesis departs from the point on how to integrate both, NFV and MEC, for different
environments and scenarios. The MEC technology is not virtualized intrinsically
hence the first part of the thesis explores the integration of MEC in NFV environment.
Initially a MEC application and the utilization of radio context information is showcased
through an Edge robotics scenario. Later the full integration of virtualized MEC components
within an NFV infrastructure is elaborated through categorization, and proposed
solution in tackling integration issues. Further, a tutorial is presented on how the exemplary
Edge robotics would be deployed, terminated and managed in an MEC in NFV
environment. The elaborated procedures present high compatibility and readiness for
MEC in NFV future deployments. The findings are compared with existing works on the
similar topic.
The joint, or horizontal, integration of MEC in NFV is referred to a single administrative
domain. The rest of the thesis is focusing on how administrative domains are able
to fulfill vertical requirements by deploying end-to-end services across multiple domains.
One of the thesis contribution is towards the definition, characterization and classification
of federation - the process of deploying NFV services across multi-domain scenarios.
Further the federation scenario is showcased in a static environment for a novel missioncritical
eHealth application. All the federation functionalities are demonstrated in a realcase
experimental emergency scenario for a patient suffering from a heart-attack. The
assumption is that the federation occurs between two administrative domains enabling end-to-end AR/VR emergency services spread across two NFV based infrastructures. The
obtained experimental results provide improvement in the future emergency events while
leveraging on novel technologies such as AR/VR. The drawbacks are evaluated accordingly.
The use of both MEC and NFV enables better user experience, customized networks
and it is a big step towards automation, and reactive network life-cycle management. The
following part of the thesis focuses on how to apply the federation concept in dynamic
environments - where the conditions change rapidly, the resources are volatile and the
relationships between administrative domains are established on-the-fly or unexpectedly
broken. Blockchain as a Distributed Ledger Technology (DLT) is applied to facilitate
and build trust in the brief negotiation process between mutually unknown administrative
domains. A concrete step-by-step process is proposed which its application, in orchestration
and life-cycle management (e.g., healing process), of emulated NFV service
has been experimentally evaluated across multiple Blockchain platforms. Additionally,
the Blockchain solution is applied in a small-scale Edge robotics experimental scenario.
The Edge robotics service is a MEC-in-NFV based remote control application for mobile
robots which leverage the DLT federation to extend the robot driving range by deploying
radio network extension on top of an external domain infrastructure, without any interruption
or downtime of the end-to-end Edge robotics service.
In the last part of the thesis the focus is set on how service provides or telco operators
may increase their profit margins by leveraging the federation process and using Machine
Learning algorithms to generate a profitable decision of whether to federate a service or
deploy the service over the constituent infrastructure. The application of Reinforcement
learning algorithms such as Q-learning provides a promising near-optimal results. These
are improved with the application of Deep Q-learning techniques through the use of real
dynamic price fluctuations for service offerings.
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Keywords
5g networks, MEC, Multi-access edge computing, NFV, Network function virtualization, SDN, Software-defined networking, Federation, Machine-learning