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AI will design tomorrow’s networks

What impact will AI have on designing the networks that keep people and businesses connected in the future? What will those networks be capable of?

By James Nunns

Of all that is written about artificial intelligence (AI), one of the resounding conclusions is that AI, machine learning and automation will increasingly take on functions within society and business that were once the reserve of skilled human beings – and in some cases, highly skilled human beings.


Setting the arguments for and against this evolution to one side, what we will see is a democratisation of skills which will has the potential to overcome some the most complex engineering challenges known to both man and machine. What impact will AI have on designing the networks that keep people and businesses connected in the future? What will those networks be capable of?


Democratising skills with algorithms

Designing a network is one of the most incredibly complex feats of engineering known to man. There are only a few people on the planet who have the necessary skills, knowledge and experience to embark on such a project. One argument in favour of using AI to help improve the network design process is that this knowledge, experience and skill becomes accessible to the many rather than restricted to the few. By pouring all our existing expertise, data and research into an AI algorithm, this knowledge can be shared and used more creatively as well as augmented and developed further.

So, not only will the number of people and companies that are able to build and innovate with networks increase, the networks which are designed and developed will be capable of far more than their predecessors.

Read more: Highest Paying Networking Jobs 2017

We are already seeing networks becoming increasingly complex due to their global and multi-layered nature, with wireless networks such as superfast 4G or Low Power Internet of Things (IoT) networks built on top of the global fibre IP backbone. A couple of years ago, you could have argued that network complexity was increasing faster than the rate of technological innovation. However, AI is the key to designing networks which are future proofed against the increasing demands new technologies such as autonomous driving, virtual reality and the IoT will put on the world’s networks.

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If it ain’t broken…

While the process of designing a network is highly mathematical and logical, it is still “human” in the sense that somebody does it. This person, amazingly talented as they are, is still prone to human facets such as habit, personal preference and bias. They say “old habits die hard” and psychologically humans are pre-disposed to continue with ways of working which have stood them in good stead previously. This is summed up by another idiom: “don’t fix it if it isn’t broken.” These predispositions as well as other variables such as time and budget restrictions can prevent humans from weighing up every single possible alternative when they are already aware of a process which has worked just fine in the past. The natural inclination is to focus on the things which are in most obvious need of improvement. This is what sets humans and machines apart.

Machine learning will overturn the human approach to design and find ways of designing networks which are faster, more cost-effective and produce better results than we are currently capable of. The sheer relentlessness of the computing power with AI will achieve means that there are potentially design and management techniques which humans are yet to discover, but self-improving intelligent algorithms will harness over time.


More intelligent approaches to networking

As well as designing the network, AI will help manage, maintain and protect it. Right now networks are monitored by algorithms which look for anomalous build-ups of traffic and activity which may be the result of malicious activities such as Distributed Denial of Service (DDoS) attacks and attempted hacks. As the AI powering these algorithms becomes more intelligent, it will find faster and more fool-proof methods of anticipating threats and cleaning the network. Another example is that AI will be able to better predict traffic as it collects and analyses data in real-time, meaning network managers are better prepared for big events such as the Olympics, Black Friday and Singles Day, which often put the Internet under pressure.

AI will also play a central role in software-defined wide area networks (SD-WAN) of the future. It’s still a nascent technology but SD-WAN is set for huge growth: Gartner predicts that by 2018 more than 40% of WAN edge infrastructure refresh initiatives will be SD-WAN-based, up from less than 2% today. Empowered by AI, an SD-WAN allows enterprises to deploy a new kind of hybrid network that combines the scalability of the Internet with security and reliability of a private network. The ability to automatically and dynamically route traffic between the Internet and the private network, ensures that employees are able to enjoy superfast, secure access to applications and data to collaborate securely and seamlessly, wherever in the world they are.

Read more: Businesses should adopt software-defined networks for data protection, says Juniper Networks

With this combination of AI-designed underlying network topologies and AI-driven software defined networking we will eventually see more profound evolutions of what networks are capable of. One idea is that of a universal network – a living, breathing global ecosystem.

Today, telecoms service providers and mobile operators strive to deliver an “always-best connected” experience to consumers. However, no matter what levels of automated switching and offloading capabilities are programmed into networks, they still don’t actively “think” for themselves.

AI has the power to radically change this, enabling us to move away from a traditional distributed network matrix. The ubiquitous network topology will emerge thanks to AI. Everything will be connected everywhere we will be able to connect data anywhere. We will no longer have to think about whether we are using Wifi, a mobile network, Bluetooth, or one of the many IoT network technologies. It will just work. Ultimately, we won’t need a mobile phone, a wearable or any other device to access this connectivity universe – our innumerable applications will become a virtual platform as we interact with them or even put them on our bodies.


Meeting the needs of the digital world

Of course, this would require a lot of work to be done by us humans first. Creating a world where all networks work harmoniously together to give all consumers a best-connected experience is a task that the telecoms industry must work together to achieve in a way that is mutually beneficial to everyone in the global network ecosystem and consumers. We need to see continued investment by all players in global networking to ensure that the infrastructure and systems that people and businesses rely on will be able to keep up with their growing digital demands. Imagine a universal network that can make decisions for you based on your location and activity – seamlessly routing you to the best possible network to handle the task you are carrying out without interrupting your experience. Within this world, AI would be the facilitator of real-time conversations between networks ensuring that all interactions are receiving the best-possible quality of service out of the connections available to them.

In summary, I expect the impact of AI in the design, management and protection of future networks to be radical. However, as well as the more functional, operational elements, the advent of AI provides a huge opportunity to revolutionise the world’s networks. This is particularly important when one considers that we are at the tipping point where the things we use networks is about to change forever, thanks to things such as IoT-enabled autonomous vehicles and always-connected smart city systems.

In this context, will AI prompt a total rethink of whether the current business models are conducive to providing the best possible user experience and the most cost-effective way possible? Because if it does, that truly would be a profoundly positive impact of AI on our industry.

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