Modern businesses rely heavily on data to provide significant business insight and real-time management over crucial business operations. Large chunks of data are routinely acquired from sensors and IoT devices running in real-time from remote places and harsh working environments practically anywhere in the world, and today's organisations are immersed in an ocean of data.  

However, the way organisations handle computing is changing due to this flow of data. The traditional computer architecture, which is based on a centralised data centre and the internet as we know it, isn't well adapted to transferring continuously flowing real-world data. Bandwidth constraints, latency concerns, and unpredictably disrupted networks can all sabotage such initiatives.  

"Around 10% of data generated by businesses are created and handled outside of a traditional centralised data centre or cloud. Gartner expects that by 2025, this figure will reach 75%."  

This is where edge computing architecture comes in and helps businesses address these data concerns. To put exactly in the words of IBM: Edge computing is a distributed computing framework that brings enterprise applications closer to data sources such as IoT devices or local edge servers. To be precise, an entity's data is processed and analysed closer to the point where it is created.   

Edge computing and 5G - the combo  

5G is enabling an era of user-centric networks by bringing in the concept of network slicing and composable networking. This has caused a fundamental shift from "network-aware application design" to "application-centric network provisioning". As mentioned in a Wipro blog, it marks a major step in network architecture.  

The Department of Telecom under GoI made clear that the government is planning for the 5G spectrum auction early in June this year. Edge and 5G are mutually beneficial. Edge computing — particularly on 5G networks — provides faster and more thorough data processing, allowing faster response times, deeper insights, and better consumer experiences.   

Also, 5G has a beneficial impact on enterprise edge adoption because it allows for the installation of lower-power but faster computes power. In addition, the problem of latency comes down considerably as the data is not required to travel over a network to a data centre or cloud to be processed.   

Edge computing in the industry will be expanded by 5G, allowing businesses to analyse enormous amounts of data on devices (or on-site) in near real-time. Large industrial enterprises, for example, can use edge computing to boost production dramatically. In the automobile industry, 5G and edge computing will aid in the development of connected and autonomous vehicles. Many other industries can benefit from the integration of AI, IoT, virtualisation, 5G and edge computing: 

  • Telecom and OTT streaming services operators  
  • Oil&Gas  
  • Disaster recovery and Defense  
  • Transportation and automotive  

Additionally, the fusion of artificial intelligence and edge computing has resulted in edge AI solutions.

  • Edge AI ensures that the factory floor is productive and safe in the manufacturing industry. It is feasible to check product quality with incredible precision by incorporating machine vision. It also aids in product automation and mechanical failure prediction.   
  • Edge AI enables hospitals to work smartly without worrying about the security of data. They are used in the medical industry to do tasks like high-precision thermal screening, disease prediction and remote patient monitoring.   
  • Drones using Edge AI are used in a range of situations, including construction, cartography and even traffic monitoring. Drones are used for visual search, image recognition, object detection, and tracking.  

 Critical for future  

Furthermore, the volume of data consumed has increased tremendously as a result of the introduction of technologies like artificial intelligence, machine learning, 5G and even blockchain. By 2025, there will be 41.6 billion IoT devices linked, generating 79.4 Zettabytes of data, as projected by the International Data Corporation (IDC).   

As a result, processing this much volume of data will necessitate a massive amount of combined computational power. Large data centres' workload will be lowered if one switches to a distributed system with intermediary nodes, which will improve the processing of all those requests. As a result, edge computing is key.  

However, one has to remain careful before treading on this path. Like any rapidly emerging technology, Edge computing solutions come with risks when it comes to evaluating, installing, and running them. They come in a variety of shapes and sizes, but one of the most important is security. Another issue to consider is that the expense of implementing and managing an edge computing infrastructure can rapidly outweigh the project's financial benefits. 

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