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Harnessing network slicing for disaster response

(Image credit: Image Credit: Flex)

Over the last thirty years, Europe has recorded a 60 per cent increase in extreme weather events—and there is no sign of it slowing down. While the UK and some parts of Europe may view extreme weather as something that happens elsewhere, shifts in weather patterns are changing this assumption. More intense heat waves and droughts, increasingly severe storms and flooding, and freezing winter temperatures are, and will continue to become, more common.

While extreme weather events throw challenges from a human and infrastructure perspective, for the telecoms industry, these can also present challenges from a telecoms and communications perspective. A key part of disaster response is communication between the teams of emergency and rescue services. While much of the conversations around 5G focus on increased speed and bandwidth, there are some less-hyped aspects of the technology that will be essential in keeping people safe in times of peril.

Dedicated disaster networks

Communication is critical immediately before, during and after a crisis, and enabling emergency response teams to coordinate and share critical data can be the difference between life and death. Yet, every service, operator or company that uses a mobile network has to share the network’s resources, in spite of the fact that certain types of communications may be more urgent and important than others. What’s more, other factors such as capacity, latency, security, power consumption and geographic coverage tend to vary depending on the end-user; in the case of emergency services, they will need high-capacity, extremely low latency coverage that can extend across a vast geographical space or region.

To allow this to happen, emergency services need to have priority over others using the network. While allocating ‘special’ resources to emergency services may have been more difficult with previous wireless generations, with 5G comes the ability to create individual network slices, or individual virtual networks that can be optimised for a particular service. This could be a slice, or multiple slices, allocated to a specific service—such as emergency and rescue services—to meet the capacity, latency and security needs of emergency responders, without the fear of network lag, or drops in network coverage.

It’s also critical that these network slices can support the bandwidth activity required from emergency responders. For example, they commonly wear bodycams and carry wearable health sensors to track body temperature, heart rate, motion, etc. All of this data, plus real-time data from weather maps, satellites, radars, weather stations, and social media can be critical to understanding exactly what is happening during an emergency and plan the appropriate response. Transmitting, correlating and analysing this volume of data in real-time can place great strain on the network, but by employing network slices, operators can ensure that emergency responders get the network capacity they need, particularly in times of crises.

Assuring QoS at all times

While network slices solves the network resourcing conundrum, it throws up challenges in assuring each network slice and guaranteeing network QoS. Sliced 5G networks are incredibly complex, making it very challenging to manually detect, identify and resolve issues that may occur across the network, within each slice.

To address this issue, more operators are looking beyond simple automation and towards AI and machine learning to guarantee QoS. Advancements in AI and machine learning are providing operators with the tools to correlate and analyse a huge number of data sets spanning the entire network and its slices. This allows them to seamlessly identify and resolve issues before they impact the end-user. Machine learning, for example, can be used to identify patterns and allows operators to shift from reactive to proactive in identifying underlying issues that are yet to affect the network. This pattern detection can then be used to trigger automated responses to resolve issues occurring across the network or within a particular network slice. In the event of a disaster, being able to assure network QoS on a per-slice basis will be crucial to ensure that emergency responders can communicate and share data and information with their teams.  

New 5G networks will create a wealth of opportunity for operators to enhance how we communicate. For emergency responders, this will be crucial in enabling them to be as efficient as possible during emergency situations. But harnessing the powers of 5G will require operators to rethink how they approach service assurance. 5G slicing will create even more complexity and will require operators to assure not just one network, but multiple virtual network slices, each with different requirements and SLAs. By embracing automation and turning to AI and machine learning solutions for service assurance, operators will be able to assure network QoS in a way that meets the needs of the end-user. For an emergency responder, being able to rely on future 5G networks will be critical, and after all, it’s something we’ll all be thankful for.

Yuval Stein, AVP Product Management, TEOCO

With more than 15 years of experience in the service assurance domain, Yuval has held key product management positions throughout his career. He brings his knowledge to the fault, performance and service domains, and uses his hands-on experience to adapt service assurance solutions to the industry challenges: digital services and network technologies.