Just imagine, instead of 70, your heart rate was at 100 beats per minute. This could be a warning sign that you are on the verge of having a heart attack.

If your doctor were to get this  information in real time, they could check the readings against your medical  records and see that this is completely out of the norm and then warn you to seek  medical assistance immediately. However, if your personal trainer received that  same information, would they reach the same conclusion as your doctor? Your  trainer has access to a different database, which might show your resting heart  rate as well as the rate during high-intensity training. Knowing that you are likely  exercising, they would instead conclude that there is no need to go to the  hospital after all.

This clearly demonstrates that just  accepting raw data without filtering and proper analysis is no longer good  enough and can potentially have serious repercussions. Instead, it is critical  that we have diversity of thought when it comes to how we interpret data. This is  not just true for our health or other day-to-day scenarios, but can also be  applied to the communication networks that carry and house our information.

To achieve this, the network must not  only be autonomous at some level; it needs to be able to adapt, configure and  maintain itself constantly. But note - with increased automation there is a  risk that the network can become too rigid and potentially take inappropriate  action without assessing the wider context.

This is why we need networks with ‘intent-based’  control that take advantage of software automation without relinquishing  complete control. Intent-based control will help guide the network to react appropriately  to changing user demands and unexpected issues. Now more than ever, we need to  make sure that our networks are not just autonomous, but adaptive.

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European  operators are adapting now

European operators are preparing for  the vast connectivity required for the internet of things (IoT), and 5G – the  technology that will support real-time access to, and sharing of, information  like health records between your trainer and doctor. But this is not without  its challenges. Being connected is becoming cheaper; while IoT and mobility are  pushing zettabytes of data per year. Demand is far outpacing fixed line  connectivity, and the revenue from these data services continues to decline.

Business users are moving from buying  individual products to purchasing services, like access to cloud-based  solutions. And at home, users are after convenience, which is driving the  convergence of fixed lines, TV and broadband. There is also a more intent focus  on increasing broadband investment, and the quest for rural broadband continues  – such as the EU's ambitious initiatives to provide half of European households  with at least 100Mbps by 2020.

So, operators are having to seek new  opportunities, expand into new areas, extend their product sets, and embrace  cross-industry partnerships. In essence, they are adapting; converting from  offering single mobile, voice and data services to a full range of converged  services incorporating mobile and fixed-line services as well as content and  digital media.

Key  Aspects of the Adaptive Network

An Adaptive NetworkTM leverages artificial  intelligence, machine learning and software analytics to examine the many data  points being generated at any given time so that the network can react to end  user demands and adjust without human interaction. This is possible thanks to  sophisticated software capabilities that uncover deep, meaningful patterns in  data or content to help organizations – or in this case, their networks – make  intelligent decisions.

Built upon three key elements –  software control and automation, analytics and intelligence, and programmable  infrastructure – the Adaptive Network allows network operators to evolve their  current infrastructures so their network becomes a communication loop that  relays information from network elements, instrumentation, users and  applications, through to a software layer for analysis and action.

The Adaptive Network diagram

EMEA  operators are taking this path now - moving from evaluation to adoption of new  networking technologies. On the most part, avoiding large-scale rip and replace,  and choosing consistent and steady evolution that perfects one change before  moving to the next, adapting and learning all the while.  We  are seeing operators take up new partnerships to serve future high-bandwidth  demands, pioneer new levels of network-to-network interoperability, move to  multi-layer, multi-vendor solutions, and enabling new services such as allowing  enterprise customers the ability to instantly provision virtual network  functions (VNF) on demand with self-service ordering capabilities.

EMEA operators are taking this path now - moving from evaluation to adoption of new networking technologies. On the most part, avoiding large-scale rip and replace, and choosing consistent and steady evolution that perfects one change before moving to the next, adapting and learning all the while.

By embarking on this journey to the  Adaptive Network as an evolution, these operators are going beyond autonomous  networking; making their infrastructure more programmable and intelligent one  step at a time, allowing the network to be flexible and grow with the company  and their needs. These operators also realise that to make the Adaptive Network  a success, it is important to have a choice of providers and that the  automation software works across multiple vendors. By embracing openness, they can  select the technology that best meets their needs when it comes to operational  fit, performance, power consumption and telemetry. This will result in sharp  reduction of costs, increased agility and a highly flexible network  architecture that can evolve to take advantage of any future innovations.

It’s  about interpreting the data

Data, both big and small, has an  impact upon all of us, and to use it to our greatest advantage, we should  analyse it appropriately. Just as a doctor and personal trainer must analyse  your heartbeat differently, the network needs to be intelligent and flexible so  that it can gather both small data (things that happen very quickly, like a  customer’s heart rising abnormally) and big data (key trends that allow the  network to anticipate failures before they happen) and then makes policy-based  decisions. The Adaptive Network can do this. For example, one of the policy  choices may be to allow human review and/or intervention, which a completely  autonomous network doesn’t permit.

By ensuring there is a human element  behind networking control and management, the Adaptive Network will identify  problems before they occur, whilst ensuring optimal control by an experienced  technician. This will allow network providers to offer networks which boast  speed, efficiency, and reliability.

As traffic from mobile broadband and  IoT increases, there will be a surge in the amount of data passing through operator  networks. To ensure they can cope with these rising demands, operators will  need to forge more effective partnerships between humans and machines, to create  agile and adaptive networks that can overcome emerging market challenges, today  – and tomorrow.