Using machine learning to optimise networks

Using machine learning to optimise networks

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How Kollective’s enterprise content delivery network can save businesses valuable time

Guest contributor |


With promises of boosting efficiency, reducing costs and increasing profits, machine learning and artificial intelligence technologies are leading organisations to re-evaluate their operations. A 2021 McKinsey survey found that 56 per cent of companies now use ML in at least one area of their business. Additionally, 27 per cent of respondents credited AI and ML for contributing at least five per cent of their earnings before interest and taxes. 

At Kollective, we understand the value of ML, which is why we developed the world’s first and only smart enterprise content delivery network (ECDN), which utilises ML to optimise network bandwidth and content delivery. 

Network quality is of particular importance during live virtual events. Businesses only have one chance to get it right, which is why they must assess their network’s ability to handle high volumes of concurrent streams before events. Kollective’s Smart ECDN eliminates any uncertainty and doubt by running silent tests that construct a detailed model of the ideal network configuration. Users don’t need to be an IT expert to configure their network to stream flawless live videos.  

Smart ECDN also features a smart diagnostics capability to recognise anomalies in a network. Our ML protocols examine patterns of data playback that meet certain expectations. Our anomaly detection algorithms recognises when something unexpected happens on a network and flags the event. This helps businesses prevent network issues that might lead to prolonged downtime, thus providing a smooth and continuous experience for users.  

Our system automatically investigates the cause of flagged behaviour and surfaces insights in a smart diagnostic dashboard. The system then informs users of the location of the issue within the network, identifies affected users, and provides a solution to prevent future occurrences.  

One of the most significant advantages of Kollective’s Smart ECDN is its ability to constantly refine a network over time. Our ML algorithms learn the network’s patterns and behaviours, leading to highly accurate recommendations. This reduces downtime and troubleshooting time and enables businesses to continually improve their network performance.  

As businesses steadily uncover the potential of ML and AI, adoption continues to climb. Kollective’s Smart ECDN is our first step into this realm as we continue to seek new and innovative ways to create the best possible experience for our customers.  

Garrett Gladden is senior vice president of product management at Kollective   

This article was originally published in the Spring 2023 issue of Technology Record. To get future issues delivered directly to your inbox, sign up for a free subscription

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