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The coming together of 5G, with Edge and AI, is critical for Industry Convergence
The coming together of 5G, with Edge and AI, is critical for Industry Convergence

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Communication Service Providers (CSP) are unleashing their 5G plans globally, while complementary functions of Edge Computing and AI are increasingly empowering enterprises across industries. These emerging forces will need to come together rapidly to accelerate cross-industry use cases, both towards consumer and business segments, to create new business models and revenue streams.

CSP strategy with 5G rollout - 5G deployments are envisioned as next-generation technological enhancements to the wireless access, transport, cloud, network operations used in telecommunication networks to incrementally build on 4G technologies which are currently deployed. Rolling out of 5G infrastructure is expensive and CSPs are proceeding with caution to protect their existing investments in 4G. With 5G, CSPs will be able to combine elements of 4G and 5G as they see fit.

Hence, the initial set of business cases would look at provisioning higher bandwidth and lower latency to cater to increased mobile traffic with only a limited revenue uplift. The real focus for CSPs will shift to enterprise use cases like connected cars, connected shopfloor, smart homes etc due to changing business priorities aimed to drive higher revenue.

The coming together of 5G with edge computing and AI will be a game changer – While the promise of 5G is high-speed, large volume transfer of data, there is a parallel technology architecture component emerging around Edge. With the Edge architecture, systems will have the power to deploy, run, manage and maintain application work-loads closer to the source of data. Software components like Edge Application Management systems combined with Cloud, Edge Devices and Network to ensure those software work-loads that need to be fed large volume/ heavy/ fast-turnaround data sets, are placed closer to the source than the Cloud Data Centre. In simple terms, instead of taking large data sets to the Cloud, parts of the Cloud application are made available at the Edge.

Fig 1 :5G Ecosystem  - confluence of 5G, Edge and AI (Source: IBM Institute for Business Value)
5G Ecosystem  - confluence of 5G, Edge and AI (Source: IBM Institute for Business Value)

 


 

 

 

 

 

 

 


Typically the requirements that drive the need for such data volumes and speed are also the ones that require decision-making and more often than not, need software work-loads involving Analytics and Artificial Intelligence. For example, consider the needs in an Automotive paint shop to inspect the post-operation quality. The volume of data and speed of response are both high here, needing Computer Vision solution to analyze and provide a recommendation within 10s of seconds. All the raw data need not be transported all the way to the Cloud either immediately or at one time. Same would be the case in a patient-care scenario, or in case of high-speed rail related use case. Another example would be drones carrying specialized equipment and interacting with IoT enabled environments to deliver advanced analysis and automated actions towards potential remediation like medical emergencies or for law enforcement or even for remote diagnosis/repair.

Thus the combination of 5G, Edge and AI is becoming an articulated need.

The Architecture thus begins to offer these software work-loads on either of these Edge nodes:

  • Device Edge: Cameras or similar devices come with compute power that can run small applications to make decisions
  • Device Edge (Edge Cluster): Between multiple devices in one location/ site, there could be a small processing DC/ Server that can receive and process information from these local devices
  • Infrastructure Edge: In the Network DC, there could be a processing of work-loads instead of taking the data all the way to the Cloud

All of the above along with 5G, power the traffic, and components like Edge Application Managers ensure the integrity of the work-loads at the edge in relation to the central version on the Cloud.

New business models with 5G, Edge and AI are leading to industry convergence. Having the cloud compute function at the edge, either device edge or network edge, allows high intensity transactions to be processed seamlessly with lower latency and enhances the 5G network performance. This leads to a set of exciting use cases around autonomous driving, AR/VR gaming, remote patient monitoring, remote robotic surgery, smart metering, digital signage for retail shops, improving equipment accuracy, improving driver safety, smart farming driven by AI enabled monitoring – the list of use case is endless. This is the driving force for the next industrial revolution or  Industry 4.0. AI has made edge devices increasingly smart, thus allowing devices to provide insights and predictive analysis in real time, as well as drive local decision-making.

For CSPs to drive their automation journey, will need to consider these points to optimize, enhance and accelerate.

  • Move away from lock-in to legacy telecom network devices all of which have proprietary hardware/OS.
  • To have the VNFs (Virtual Network Functions) containerized to run on commodity hardware and leverage the unlimited compute of open cloud to bring in scalability and faster Time-To-Market, thus enabling multi-cloud with portability across private and public clouds.
  • To bring in automated network orchestration to enable quicker onboarding/orchestration using third party VNFs to deliver a completely new set of services like network slicing for a factory and embed AI in the network for a self-healing network.

All of this will now enable creation of market making platforms using exponential technologies like IoT, cloud compute and edge to drive creation of new revenue models.

In summary, 5G with AI at the Edge will power smart consumer and smart enterprise applications. CSPs have the advantage of the trust of their customers which they will look to leverage for monetizing within the ecosystem.
 

This article is co-authored by:

Subrata Ghosh
Subrata Ghosh
Industry leader, 
Telecom, Media and Entertainment, IBM India                                
Srinivasan Rangachary
  Srinivasan Rangachary
  Intelligent Connected   
​​​​​  ​​Operations Practice Leader,
  Globally Integrated   
  ​​​​Capabilities, IBM 

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