Networks generate extraordinary outcomes. This is ancient knowledge. Our rulers knew this. Chandragupta Maurya, who established an empire across the Indian subcontinent, for example, built a massive highway along what was then the Uttarapath (Northern path). For approximately 2,300 years, his 2,400 km highway linked what we today recognize as Bangladesh in the east to Afghanistan in the west. It networked communities from cities that later came to be known as Chittagong, Amritsar, Rawalpindi, and Kabul. It made travel, trade, and communication (via postal services) easier. Today, we know this highway as the Grand Trunk Road, an extraordinary creation of infrastructure. But it was Chandragupta Maurya’s grandson, Emperor Ashoka, who understood how to make the network deliver exponential results. He planted trees along roads to give shade to men and animals, dug wells, and built rest houses, hospitals, and even pharmacological gardens to make the network safer and easier to use. The assets he added to the highway became nodes where people stopped, met, exchanged information, and curated knowledge to stimulate collaboration and competition. In a world of exponential change, we need to ponder more on how networks have a compounding effect.
Before diving into enterprise networks (of the LAN, WAN, VPN, MPLS, SD-WAN, Wi-Fi 6, 5G, type) and their relationship with intelligence, it helps to recognize that various types of networks are being used everywhere to solve hyper-scale problems. Some examples include the ongoing attempt to distill and validate the knowledge of billions of people about everything on planet Earth and beyond in over 300 languages (Wikipedia); the search for extraterrestrial intelligence (NASA’s SETI program); and crowdsourcing democratic legislation (Pol. is used by Taiwan). For those who are curious, the Augmented Collective Intelligence Database provides a thought-provoking look at over 775 organizations using digital technologies to augment networks and create a better world.
Networks that stitch technology together have become complex. They incorporate autonomous and connected vehicles, IoT devices, drones, peripherals, and wearables intrinsic to the metaverse, enterprise data, transactional data, access to software and operating systems, etc. And this we know with certainty: Where there is data, there is intelligence. The question is, “Are enterprises doing enough to tap that data to dynamically control and re-shape their networks?”
A classic example of leveraging intelligence in networks is evident in mobile infrastructure. As the technology of mobile networks changed from 2G to LTE/ 4G, these networks supported services beyond voice calls and SMS. They now deliver video and real-time transaction information on any device, anywhere. But we cannot have only fatter pipes to meet growing traffic. They inevitably get congested in a few years. We need intelligence in the networks to assess what is happening in them. This knowledge can drive the optimal use of resources, nudge users into desired behaviors, improve the Quality of Service (QoS) and provide personalization.
Imagine a situation in a manufacturing plant where surveillance cameras are used to observe activity. Some buffering may be permissible in normal conditions, with negligible impact on the observation. But there could be emergencies, say a security breach, an accident, or an equipment malfunction, when buffering can seriously impede action. In such instances, network intelligence should be able to dynamically increase the bandwidth available to the cameras without affecting other demands. 5G networks do this by using network slicing, where several virtual networks exist on the same physical infrastructure.
Another example of intelligence in 5G networks is the ability to maintain QoS through beamforming. QoS in a mobile network depends on the device’s distance from the base station. QoS can be maintained or improved by increasing the density of the base stations. This requires linear investments. Instead, 5G networks manage this problem intelligently. Their nodes steer dedicated beams to users, directing signals where they are needed. For example, if demand steadily increases in the business district of a small city through the morning, beamforming directs the signal accordingly. By evening as people return to their suburban homes, the beams redirect and redistribute capacity.
The services that today’s programmable and intelligent networks can create are limited by the imagination. Many organizations that once saw networks as a cost –or as inescapable connectivity — are starting to view them as enablers of innovation and new business models. Networks that were once designed to meet straightforward business requirements are now under pressure to support innovation, strengthen security, lower costs and drive governance. Intelligent networks are even more critical in a world where hybrid work models are the future. User expectations are rising. Organizations must tap into network intelligence to dynamically manage services, provide scalability, and lower disruptions to meet user expectations and business goals.
