Racing to the “Edge” with 5G enabled IoT

Are we there yet?

As I walk away from my computer at the end of a workday, having spent several hours in online team meetings, presentations and research calls – there is a moment of reckoning – of our lives being transformed in an irrefutable way for the better not worse. The COVID-19 pandemic has shown us that the service and operational strategies of rendering digital content and other solutions via cloud network by telecom operators is rapidly changing. Our homes are becoming the new edge as we work, study, play games or binge-watch endless hours of the new Netflix or Amazon Prime web series on the telly, from the comfort of our lounge. With media technology developing at a frantic pace, and as video formats such as 4k and 5k make their way to consumer devices, the bandwidth delivery methods must be optimised to handle such heavy data loads. Did you know that an average 10-minute-long 60 frames per second 4k video streamed on YouTube, uses approximately 4GB of bandwidth! One of my previous articles, provides details on how IP network traffic is literally bursting with demand during the pandemic.

Moving on to industrial businesses, as they continue to embrace digitisation, several IoT use cases have emerged as major strategic drivers and fundamental transformation agents – many of which, directly influence our personal lives providing us with digital contact tracking, real-time automation, monitoring and tracking, hazard and maintenance sensing, smart surveillance and several other benefits. The rise of IoT applications and services has been fuelled by a confluence of technology trends including: rapid declines in the cost and increases in the power of computing – leading to a proliferation of cheaper and more powerful sensors and devices; advancements in network connectivity, especially 5G – which will be critical in IoT to both telecom service providers and vertical industries alike; and mainstreaming of cloud technology – which makes computing very elastic. Most importantly, to drive IoT you need connectivity everywhere to collect data from devices, sensors, things, etc. 

In comparison to traditional networks that have taken a very centralised approach to managing data – edge computing can be seen as an intermediate layer between devices and cloud, where services are handled by distributed edge nodes bringing primary processing and storage closer to support high-bandwidth devices and time-sensitive data – thus enabling better data control, reduced costs, faster insights and actions, and continuous operations. 

If we look at some numbers – the latest edge computing market projections by Grand View Research estimates a global value of USD$28.84B by 2025 up from $1.47B in 2018. This represents a CAGR of 54.0%. With so much promise and such large business growth potential in edge computing – the question being asked is ‘Are we there yet?’ and if not, then ‘What can get us to the edge quickly and efficiently?”. 

The potential to dramatically improve latency and bandwidth, delivering the ‘everywhere, anytime’ communications required by edge computing – is provided by 5G. Gartner estimates that by 2025, 75% of enterprise data will be processed at the edge, compared to only 10% today. This is an exciting prediction showcasing the benefits of the low latency of edge computing, and the lightning speed of 5G. In essence, it is a combination of digital content, services, applications, devices, edge computing, high-performance distributed 5G core capabilities, and 5G access networks that make will make innovations possible. 

The 5G Edge enabled IoT business opportunity

The Edge has enabled a large number of new IoT services and applications for multiple sectors, such as consumer, enterprise, and health – and has created a new value chain and an energised ecosystem, which in turn creates new opportunities for mobile operators and application and content providers. 

As per the Cellular Telecommunications and Internet Association (CTIA) for the US Cellular IoT Connectivity TAM, there will be over 270M IoT Connections by 2023. With an average market ARPU of USD$0.59 p.m this will amount to USD$1.9B in revenue per year. Adding to this is the huge opportunity of IoT Applications amounting to over USD$550B in revenue per year. Ericsson reports that by 2030 up to USD$700B of the 5G-enabled, business-to-business value could be addressed by telecom operators.

This makes a very strong case for accelerating 5G network deployments – because by leveraging the 5G network, edge computing harnesses growing in-device computing capability provides near real-time insights and predictive analysis. This increased analytics capability in “edge devices can power innovation” to improve quality and enhance value for our customers. If interested, you can click on the link to get a better understanding of innovation processes.

Designing an AI-driven IoT Application Ecosystem

The illustration in Exhibit-1, presents a contextual view of how 5G is enabling IoT and why this makes 5G and edge computing one of the most powerful technology synergies – ever.

<Exhibit-1: AI-driven IoT Application Ecosystem delivered on the 5G Edge>

Today as telecom operators become IoT providers, it’s clear that they’re embracing IoT mainly to make money. Analyst firm Analysys Mason says – telecom operators are investing in IoT for three reasons today: 1) To make money, 2) To make money, and 3) To make money! 

Future reading – My article, discussing Internet of Medical Things (IoMT) and Connected Healthcare Edge Computing, provides examples of how the IoT Application Ecosystem is being applied today.

Architecting the Telecom Mobile Edge

In February this year, GSMA announced a new initiative to develop a common telco edge cloud platform for network operators. China Unicom, Deutsche Telekom, EE, KDDI, Orange, Singtel, SK Telecom, Telefonica and TIM are participating in the project.  This is intended to make local network operator assets available to developers and software vendors to bring their services closer to enterprise customers. This is happening as operators compete to get the “Mobile Edge” computing (MEC) foundation right – and build successful IoT businesses on top of it by providing platforms, applications and services – each step adding additional value and revenue potential.  

What the MEC constitutes

Exhibit-2 below, is a MEC reference architecture model that illustrates the different systems interfacing with each other. The four MEC system level elements, MEC platform manager, MEC apps, Data Plane, Containerised Virtual Network Functions, MANO solutions, NFV infrastructure, VIMs and the Network elements are all assembled to enable edge computing. 

<Exhibit-2: Telecom Mobile Edge Computing reference architecture model>

This model is based on ETSI guidelines.

The race is on!

To compete in the edge computing devices market – last month AWS added Snowcone to its Snow Family – a small, lightweight, rugged, secure edge computing, edge storage, and data transfer device. Snowcone can be used for data migration, content distribution, tactical edge computing, healthcare IoT, industrial IoT, transportation, logistics, and autonomous vehicle use cases. During this week's AWS Telecom Symposium a 5G network evolution with AWS paper was released that is definitely worth reading. This comes as Dell, EdgeConneX, ClearBlade, Cisco and several other global players are making massive inroads into the 5G edge computing market as well. 

In addition to this:

• Nokia’s Multi-access Edge Computing now takes full advantage of the telco cloud, enabling new possibilities to serve the operator’s radio network and to co-exist with other VNFs,
• Huawei CloudEdge has a new-generation mobile broadband (MBB) solution developed based on NFV, service oriented architecture (SOA), and cloud architecture, 
• HP Enterprise has the Intelligent Edge and Edgeline Portfolio;
• Cisco has the Hyperflex Edge, and
• Ericsson’s Edge NFVI is optimised to move traffic through a network distributed all the way to the edge with the low latency, low cost, and high throughput that 5G and edge computing use cases require.

Here are three related topics for you to read – 

• 5G “Sliced-Edge” Architecture: Enabling 8 business service lines
• IoMT at the Edge – Role of Telecoms in flattening the curve
• Unlocking 5 Deep Learning AI apps with Quantum Computing

Conclusion

In conclusion, I hope that this article raises important strategic questions for your business such as: How should I go about addressing an edge computing opportunity? Which role, or roles, suit my enterprise strategy the best? How can I build a business case detailing the total cost of transforming my systems to leverage the edge? How do I build my 5G Edge architecture? What IoT opportunities must I invest in? How do I deploy my workloads to the edge in the presence of increased compute capacity? How can I use the embedded AI in my smart devices to influence operational processes for my customers and my business more responsively? Or simply – how can I monetise the edge? 

Have you worked on any Edge Computing architectures recently? Would you like to share your IoT experiences on any industry vertical? Please leave your comments and questions below, and feel free to share this post if you found it interesting and valuable.

Also, if you would like the citations for this content, then reach out.

– Ashish Kar

Author is a Chief Architect @PCCW Solutions, with 24+ years in the ICT industry and an innovation gameplanning coach. He has built a Silicon Valley innovation lab and designed several IoT application and AI-driven solutions for telecom and retail organisations. He can be reached on email at [email protected].