One of the key insights came from interactions with customers in the automotive, banking and manufacturing industries. The CIOs from these large organizations don’t want to be sold connectivity products. They don’t want the network operator to create and configure the connectivity experience.
The CIOs from Mercedes, Ford, Magna know better what their connectivity needs are and what kind of slices would be useful than the network operators serving them. They don’t want to have to spend time educating their providers so that they can design a service for them. They don’t want to outsource the optimization of their connectivity to a third party who doesn’t understand their evolving needs.
The growth in private networks implementations in healthcare, energy, mining, transportation and ports for instance, is a sign that there is demand in dedicated, customized connectivity products. It is also a sign that network operators have failed so far to build the slicing infrastructure and capacity to serve these use cases.
As a result, I proposed that network operators should focus on creating a platform for industries to discover, configure and consume connectivity services. This vision had a lot of prerequisites. Networks need to evolve and adopt network virtualization through separation of hardware and software, cloud native functions, centralized orchestration, stand-alone core, network slicing, the building of the platform and API exposure…
A lot of progress has been made in all these categories, to the point that we see emerging the first dedicated slicing solutions for first responders, defense and industries. These slices are still mostly statically provisioned and managed by the network operators, but they will gradually grow.
The largest issue for evolving from static to dynamic slicing and therefore moving from network operated to as a service user configurable is managing conflicts between the slices. Dedicating static capacity for each slice is inefficient and too cost prohibitive to implement at scale except for the largest governmental use cases. Dynamic slicing creation and management requires network observability, jointly with near real time capacity prediction, reservation, and attribution.
This is where AI can provide the missing step to enable dynamic slicing for network as a service. If you can extract data from the user device, network telemetry and functions fast enough to be made available to algorithms for pattern identification in near real time, you can identify the device, user, industry, service and create the best fit connectivity, whether for a gaming console connected to a 4K TV in FWA, a business user on a video conference call, industrial collaborating robots assembling a vehicle, or a drone delivering a package.
All these use cases have different connectivity needs that are today either served by best effort undifferentiated connectivity or rigidly rule-based private networks.
As 6G is starting to emerge, will it fulfil the 5G promises and deliver curated connectivity experiences?