Several
techno-economic drivers which are paving the way to a profound digital
transformation of the Telecommunications infrastructures. Among these drivers,
there are: the diffusion of ultra-broadband, the increasing of performance of
IT systems vs the down-spiralling costs, emerging of innovative networks and
services paradigms such as SDN and NFV, the growing availability of open source
software but also the impressive advances of Machine Learning and Artificial
Intelligence.
This
digital transformation will lead the current legacy Telecommunications
infrastructures to evolve towards the 5G (the 5th generation of network
infrastructures) as an end-to-end network and service platform: in the long
term, 5G is set to integrate processing, memory/storage and networking
resources, functions and services through a “transparent”, hyper-connected
ultra-broadband programmable “fabric”.
In
this direction, in several Standardization Bodies and Fora, an high-level
reference model is emerging, based on two main pillars: 1) an infrastructure
physical layer, which will include computing, memory/storage and network
resources (up to the edge/fog resources and even the Users’ terminals, devices,
smart things); 2) a software virtualization layer which will allow providing
high-level abstractions of all the infrastructure resources, functions and
services.
It
is well known that Software-Defined Networks (SDN) and Network Function
Virtualization (NFV) are two of the key enabling technologies. Their exploitation
in 5G will allow Virtualized Network Function (VNF) and services will be
dynamically combined and orchestrated to create specific end-to-end “service
chains” for the vertical applications; moreover the infrastructure will provide
“slices” of logical resources where to execute multiple chains to serve
applications (specific QoS requirements).
It
is also reasonable to expect that this network transformation will reduce the
costs (e.g., CAPEX and OPEX) and increase the flexibility of the infrastructure,
ensuring high levels of programmability (through APIs) and the performance and
security levels required by future 5G scenarios and applications (e.g.,
Internet of Things, Tactile Internet, Immersive Communications, Automotive,
Indutry4.0, Smart Agriculture, Genomics/Omics and E-Health, etc).
So
5G will be much more than one step beyond today’s 4G-LTE networks: it is
expected to become a an end-to-end network and service platform where
multi-level APIs will allow Operators/Providers, Third Parties or even
end-Users to create/operate “service chains”, made of elementary
services/functions component capable of meeting on-demand the applications’
requirements. As a matter of fact, 5G architectural and functional
disaggregation is one of the most debated avenues in innovation and
standardization activities.
We are witnessing a rapidly increasing in the “complexity” of the
infrastructures subjected to this process of digital transformation, a complexity which will
be too high just for human-made operators.
In fact, configuration, control and
management of current physical pieces of equipment (in most cases closed boxes)
will have to be replaced by automated processes acting over millions of
virtual/logical entities (e.g., Virtual Machines, Containers, appliances etc).
Management (e.g., Fault, Configuration, Accounting, Performance and Security)
control and orchestration functions of such future infrastructures will require
innovative methods and systems (e.g., self-organizing, adaptive control,
machine learning, neural networks, etc.) capable of using the big data to
mitigate this “complexity”.
It
is not only a technical “complexity” but also an economic one, about biz
sustainability. The increasing competition pressure in the Telecommunications
market is pushing Network Operators and Service Providers to look for new
services scenarios and solutions for reducing/optimising the overall operations
costs to compensate the cases where revenues are declining.
It is expected that A.I. (e.g., ML over actionable Big Data, etc...) will help for mitigating the "complexity" of this Digital Transformation, but what will be its impact on the networks and services platforms architectures ?
It's not just a matter of mathematical methods or algorithms, heuristics, etc.. What A.I. functions, what interfaces to what have to be standardized ?
