Edge computing - A real-time makeover to data processing

“To do great things, innovation must never stop”. Make no mistake, but technology and innovation are all primed to give us a future where the internet will have absolute power over our lives. Humans will be deeply connected with machines and things. And with this, technology will never be the same, and neither will our lives. To replace or to be replaced is what it all comes down to. Think of it this way, software and Game development companies keep upgrading to provide the customer with a better experience with time by overcoming the drawbacks of the older versions. Similarly, Edge computing is an upgrade to cloud computing. 

Edge computing technology - its origin and concept

The story started way back in 1990 when Akamai introduced the Content Delivery Network (an extensive network of specialized servers distributed across the globe for distribution of web content and media between internet-connected devices). Since then, it has evolved to what we now know as Edge computing, a term created by Cisco in January 2014.

The cutting edge computing

From the Industrial Revolution to the internet revolution and now, the Industrial Internet, machines have now become self-aware, predictive, reactive, and social. The 

Industrial Internet of Things (IIoT) enlarges the perspective and does not limit the internet just to a screen. Considering that, IoT sensors generate enormous amounts of data and send them to the Cloud, where the data is processed for AI and Machine learning processes, some of which is sent back to the device while the rest is stored. Examples are Google Drive, iCloud, Dropbox, etc. At a time when the increase in IoT devices is giving a tremendous rise to bulk data production, network bandwidth gets pushed to its limit, which results in a few challenges.

  • high latency
  • end-to-end responsiveness
  • low spectral efficiency
  • higher cost of data processing
  • higher cost of sending data to the cloud and then back
  • lower bandwidth

Rising challenges with cloud computing gave birth to the edge computing concept where the data no longer flowed to the cloud but preferably processed close to where it is. This created real-time insights supporting real-time applications with real-time data processing.  A self-driving car, drone, robots are an excellent example of IoT edge computing devices. The benefits that come along with “Edge” are:

  • Creating a culture of higher Speeds - I am not even exaggerating when I say speed is everything in a business. There's a lot of competition in the market, and it all comes down to survival of the fittest. Edge computing ecosystem crunches latency and increases network performance by processing bulk data closer to the source. It, fortunately, will give birth to new AI use cases.
  • Amplifies Security - The distribution of data processing and storage across a range of devices and this distributing nature of edge computing supports the implementation of security protocols while the network continues to work.
  • Businesses like never before can easily scale their operations with the help of a combination of IoT devices and edge computing data centers. They can provide improved services to the customers and come up with new products and services to expand horizons of enhanced customer experience, making businesses versatile and reliable.

A paradigm shift in data processing - from Cloud to Edge

The long and short of it is that it is the era of real-time networking, aka reactive computing, and quick reactions become the need of the hour. Cisco estimates that the number of devices connected to IoT will grow 50 billion by 2020. It will bring challenges like stringent latency, capacity constraints, resource-constrained devices, and uninterrupted services with intermittent connectivity - which cloud computing will not be able to address. Hence, it goes without saying that in the coming years, the amount of data sent to the cloud is going to drop enormously, all credits to Edge computing. 

Zero-latency and gigabyte experience 

In the future, the number of mobile internet users will increase beyond the limit. Thus, we are moving into a next-generation (5G) that will offer us -

  1. Zero-latency - no-latent case & machine-level communication without human interruption called the Internet of Things and a speedy social interaction
  2. Gigabyte experience - the transmission and reception will be done in gigabits per second, which will satisfy the user data rate and the network capacity demand.

Here, Edge computing will provide faster response and efficient & secure services for a large number of end-users.

Edge computing solutions for IoT

MOBILE EDGE COMPUTING (MEC), later to be renamed multi-access edge computing in the MEC world congress. Mobile devices connected to distant centralized cloud servers try to obtain sophisticated applications, which impose additional load on both Radio Access Networks (RANs) and backhaul networks which result in high latency. ETSI defined the concept of MEC as a new technology that provides cloud-computing capabilities at the network edge of the mobile network within the RAN.

CLOUDLET is a mobility-enhanced small-scale cloud Data Center (DC) that is located at the Edge of the internet. A cloudlet is rich in resources and is a trusted computer or cluster of computers that are well-connected to the internet and available for use by nearby mobile devices. It provides powerful computing resources to mobile devices with lower latency. Cloudlets represent the middle tier of the 3-tier hierarchy architecture (mobile device layer, cloudlet layer, and cloud layer) to achieve crisp response time. 

Edge computing use cases

Companies of all shapes and sizes including software and game app developers are making the most of this technology and the swelling tide of data it produces in no time. 

Turns out, an American manufacturer of stringed instruments and amplifiers, Fender, with the idea of revolutionizing musical instruments, used AWS to align the wood used to make a guitar so that the instrument wouldn’t break on the expansion and contraction of grains. Indeed, a revolutionizing thought. On the other hand, companies have been using Edge computing applications for consumer data privacy. 

Furthermore, in the Industrial sector, operations require quick responses. So, when loads of data is produced, it has to be filtered as not all can be used. Here, Edge computing is used to detect anomalies in the data. Hence, the machine understands and learns when to respond to problems and how. The use of edge computing, in this case, shows growing productivity at astonishing rates by avoiding downtime.

Ericsson, a multinational networking and telecommunications company, came up with a product that is a family of Ericsson SSR (Smart Services Routers). It provided operators with a smart, scalable, and consolidated approach that offers services like IP/MPLS edge routing and Evolved Packet Gateway functionalities for both fixed and mobile network infrastructure. This gave subscribers the freedom to access the services from any device or location. The best thing about the product, among others, is its capability to produce a low carbon footprint.

From insightful street lights to agile traffic on roads, from responsive cities to uncomplicated parking, from people living safely to cleaner air - all can be accomplished with the help of edge computing. Though we have a long road to cover, but “The Edge” will shape the world with real-time technology, for sure. Using machine learning and analytics, it will produce useful insights from data for businesses. It will transform the way people do business, alter cost structures with advancements in 5G. It works towards promising us a high-speed future. Many industry experts say, “Edge computing is killing the cloud,” and I agree. It will indeed carve its way out into our spaces, replacing Cloud. Not just yet, but soon.