Digital transformation is here and now, ushering in a whole new wave of technologies that require a smarter, more agile network to support the likes of internet of things (IoT) devices, 5G infrastructure, cloud solutions and more. With 87 percent of senior business leaders saying digitalization is a company priority according to Gartner, it’s no wonder network operators are seeking the best tools to create next-gen networks that can meet the demand for low-latency connectivity, reliability and resiliency. Let’s take a closer look at three of these technologies that are transforming networks.
Software-Defined Networks (SDN)
Over the years, legacy networks have become increasingly complex, marked by different vendor technology and multiple distributed access nodes. SDN eases this network complexity by virtualizing and automating core networks. By separating decisions about where traffic goes on a network from how it is forwarded, SDN application programming interfaces (APIs) allow administrators to control traffic directly from a centralized console without manually configuring individual switches or routers.
As a result, SDN can provide flexible and scalable network architectures for companies needing to adapt to the changing demands of digital transformation, as well as support the seamless deployment of new applications and equipment needed to support these new technologies.
Machine Learning and Artificial Intelligence (AI)
Machine learning and AI are being leveraged to power SDN analytics applications that optimize networks and monitor for predictive maintenance.
These technologies allow for a push model where data is forwarded by software in real time, which in turn improves the agility of the network. Using AI, software continually crawls the network to gather information about its virtual machines and applications. It then delivers that information to the network administrators so they can take action like whether to reroute traffic from one virtual machine to another. Most importantly, the application stores this data as a time series data set that covers the operations of the network.
Using machine learning, such applications are able to differentiate between normal and anomalous data trends. AI is then leveraged to detect and address anomalies before they become errors and affect end-users, thus preventing failures and maximizing optical network uptime.
Next-Gen White Box Technology
SDN adoption has helped to reduce the traditional vendor-lock over network equipment and given rise to open standards, open source software and source-design products to give network operators more choice and flexibility.
One of the results is white box technology, a solution that eliminates the dependance on legacy networking equipment from traditional vendors. White boxes can deliver open source information between different brands of networking equipment and, therefore, are able to provide major cost savings and network flexibility to network operators across the OSI stack.
Converging These Trends to Enhance Modern Optical Networks
Network operators will find that many software companies apply the technologies discussed here on digital data from the higher layers of a network and on specific applications for their own networks and equipment. A holistic approach to network intelligence, however, should involve a solution for addressing analog data from the optical level. After all, in a typical optical network, a myriad of devices generate valuable information. These can include optical transceivers, optical channel monitors, amplifiers, optical time-domain reflectometers (OTDRs) and reconfigurable optical add-drop multiplexers (ROADMs). As a result, network operators can benefit from customizable solutions that can spot anomalies and alert network administrators of the need for corrective action before problems or failures with optical equipment occur.
At Precision OT, we are solving this challenge with Lightseer, the industry’s first technology designed to monitor and analyze the physical layers of optical SDNs all the way down to transceivers and individual optical links. Lightseer leverages predictive analytics and machine learning technologies to monitor and alert users of optical failures and anomalies before they cause network downtime. The software also helps companies avoid vendor lock by being compatible with white box networking equipment and legacy devices. To learn more about how you can create a smarter, more agile network, contact us.