Improved Network Performance,
Insights, and Service Assurance

Leveraging the right analytics tools will deliver new real-time insights into service provider networks, help reduce customer churn and offer dramatic improvements in important areas such as service level agreements and service assurance. These areas can take on even greater importance as 5G—with its faster data connections—ushers in increased adoption of critical areas such as remote surgeries and other telehealth and vertical use cases.

Current rollout of 5G networks involves 4G and 5G network coexistence. Assuring 5G services with high throughput and speed requirements will be challenging in such environments. Depending on the application, the demands for data throughput will vary. For example, applications such as autonomous vehicles, remote surgery or massive IoT device connectivity will all require high-resolution streaming with minimal latency. AI applications like traffic classification can be applied within 5G networks to ensure that 5G traffic is optimized and served effectively.

Big data analytics can help service providers better understand new service uptake, stay keenly attuned to competitive threats and performance issues (e.g. quality of experience), leveraging a continuous and intelligent feedback loop.

Improved Business and Network Operations

Among the most-anticipated benefits of 5G will be its ability to offer network sharing via slicing and delivering network services “on-demand” and MEC. Implementing network slicing demands high levels of operational agility from the network in detecting and predicting traffic types and identifying the network slice best suited to handle the traffic. ML models can be trained to perform these functions and to monitor the performance of network slices to determine when an overload or failure is likely to occur in low latency.

Many CSPs are in the process of transitioning their current networks to software defined networking (SDN) and network functions virtualization (NFV) technology to give them the ability to dynamically scale network resources based on customer demand. This shift will reduce costs, increase network agility and improve customer service. However, intelligence from the network will be crucial in orchestrating the virtual environment. Given the complexity of the network, AI will be required to provide this intelligence. 

Threat Detection and Mitigation

As 5G unlocks a huge number of opportunities and use cases for operators with massive amounts of IoT devices, applications and data flowing through the underlying network, it also creates and raises new challenges. The additional billions of endpoints, applications and data enabled by 5G and the Internet of Things create an expanded threat surface, making operators increasingly attractive and potentially lucrative targets of distributed denial of service (DDoS), man-in-the-middle and authentication attacks, and other malicious activities.

Given the enormous amount of service complexity that 5G will bring, detecting threats and securing communications networks will become a new art and science. The automation and adaptation that analytics provides is the only means to keep up with this increasingly complex, hyper-scale threat landscape. The use of a variety of policies, advanced analytics, AI and ML tools can help service providers identify and filter out malicious activity before it has the opportunity to infiltrate their network. By understanding the evolving security landscape the new network brings, service providers can leverage analytics to manage these increased threat surfaces and reap the benefits of 5G technology. Protecting their customers, brands and reputations also protects service providers’ bottom lines.

5G and its use cases will soon be used at massive scale, enabling dramatically improved connections for businesses and consumers. Making the transition to 5G technology and architectures, as well as securing next generation networks, are at the top of many service providers’ strategic priorities in 2020 and beyond. How they go about achieving these mission-critical objectives is vital. AI-driven analytics must be a major part of service providers’ plans, whether for automated network operations using machine learning, streamlining business operations, securing networks and user privacy, enhancing the end user experience or creating new revenue opportunities.