Meeting the growing demand for connectivity
Industry Voices

Meeting the growing demand for connectivity

Szczepan Gabiec Product Manager Tranport Services (002).png

The emergence of AI heralds a new era filled with both exciting opportunities and daunting challenges in the realm of technology. Unsurprisingly, at ITW (International Telecoms Week) – the world’s largest gathering of global execs from across the digital infrastructure ecosystem – AI is anticipated to be the big theme of the event.

And discussions amongst the international connectivity market, from satellite to subsea, are likely to revolve around AI technology; how it will influence network development; how it will force telcos to work differently together to succeed and remain relevant; and how it will affect planning.

We also expect to hear interesting debates around subsea developments (security, resiliency, new routes), M&A, industry consolidation and emerging regions accelerating developments due to ongoing geopolitical circumstances.

However, the complete extent of AI’s impact and influence on networks remains largely uncharted territory. Indications point towards a substantial increase in the volume of data coursing through networks due to AI, necessitating their densification and augmentation with greater intelligence.

Recognising this trend, many service providers are already prioritising the reinforcement of their networks, particularly in built-up areas where a significant portion of AI-generated data is produced and transmitted.

The challenges posed by advancements in AI

The advancements in AI present numerous challenges for infrastructure providers responsible for deploying and maintaining the physical backbone of telecommunications networks. But, at the forefront of these challenges - and possibly the most obvious - is the imperative to ensure that networks can handle the augmented data traffic and complexities brought about by AI applications. This includes optimising network architecture, bandwidth allocation, and traffic management to prevent and mitigate congestion and ensure service quality.

Moreover, AI holds the potential to enhance the predictive maintenance of fibre optic networks by analysing fibre and network performance data to identify and address potential issues proactively before they escalate. AI can optimise resource allocation within transmission networks by dynamically adjusting capacity and traffic routing based on real-time demand patterns.

However, achieving seamless integration between AI automation systems and existing network infrastructure is a challenging and costly endeavour at the moment. It often demands substantial investments in hardware, software, and training. Consequently, careful assessment of the cost-benefit ratio of AI deployment emerges as a pivotal challenge that the industry is diligently addressing.

Staying ahead of escalating demands

With escalating demands for bandwidth and network resilience under the cosh, a few things have become clear: the importance of diversity in strategising new network deployments, and taking advantage of managed optical fibre networks (MOFN) and open Cable Landing Stations (CLSs). Let’s have a look at these key areas, starting with the advantages of MOFN:

  • Reliability. First and foremost, you can consider MOFN as something you can depend on. Service providers actively monitor and maintain the network infrastructure, meaning that any issues that arise (such as fibre cuts or equipment failures) can be addressed quickly. This naturally leads to reduced downtime and improved service availability for customers.

  • Performance. With the ability to optimise network configurations and traffic routing, service providers can ensure superior performance in terms of bandwidth, latency and consistency.

  • Scalability. In the current climate which imposes demand for dramatic growth, scalability to accommodate increasing bandwidth demands is an obvious advantage of MOFN. The ability to add additional fibre strands, upgrade equipment and adjust network configurations as needed is key to supporting growing customer requirements, without compromising major disruptions to service.

In response to recent technological challenges, we’re also seeing the emergence of open Cable Landing Stations (CLSs). What makes a CLS ‘open’ is the access to multiple service providers, therefore allowing them to serve the needs of numerous subsea fibre pair owners.

In a similar vein to MOFN, the resilience of open CLSs offers a key strength to manage escalating demand. With the ability to connect to multiple submarine cable systems through open CLSs, ISPs can minimise connectivity disruption as and when any cable outages or other disruptions occur.

What’s more, they also invite the option to choose between a variety of subsea cable systems which all offer different routes and capacities, allowing companies to choose the cable(s) best suited to their changing needs and capacity demands.

All in all, there’s no doubt that we’ll be seeing the take-up of AI services within the telco space, likely in the not-too-distant future. With this in mind, businesses must have a sound understanding of both the benefits and challenges that such technology brings to hit the ground running in the AI arms race.

With the recognition of the value of diversifying network deployments and other advantageous technologies, telcos will be able to meet the growing demand for connectivity and reap the benefits.

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