Each device—from a smartphone to a smart fridge and a sensor in a remote location—will now have to compute some amount of data itself. This revolutionary paradigm, known as edge computing, is rapidly transforming the way our devices and configured and networked. But why is edge computing gaining such prominence? Here are two scenarios that endorse the increasing importance of edge computing.
Delay by a few milliseconds can cause a catastrophe: A delay in 500 milliseconds can cause a 20 percent drop in website traffic and revenues, 343 milliseconds of delay can cause an automatic car to collide with a pedestrian 35 feet away, and a 100-millisecond delay can cause a one-percent decrease in e-commerce sales. That is why enterprises need the power of edge computing to counter such delays and gain near real-time insights.
Managing millions of endpoints is beyond traditional technology: By 2021, there will be one million new IoT devices sold every hour, and by 2022, US$ 2.5 million will be spent every minute on IoT. Imagine the investments that enterprises will have to make to ensure cloud platforms are robust, scalable and fail-proof to operate these millions of endpoints! Even if they do manage to enhance cloud capabilities, these enterprises will not be able to match today’s intolerance for latency or negate heightened risks of downtime and inaccuracies. As the IoT network encompasses different endpoints—multiple devices, mobile phones, and point of sale systems— security also becomes a major concern. Analytics and business intelligence solutions will also take a hit if millions of devices depend on one intelligent cloud application to make decisions for them. This is where edge computing literally has the ‘edge.’
Edge computing: The next in digital transformation.
By enhancing data storage capabilities, securing customer’s privacy, accelerating automation, catalyzing product personalization, and offering instant insight-based decisions; enterprises stand to gain through edge computing. Here, I have elaborated on how edge computing provides three primary benefits:
Understanding customers better and offering hyper-personalized solutions: By deploying cloudlets that are relatively smaller than clouds, enterprises can process data closer to devices and ensure greater security and privacy of their IoT networks. Imagine that you visit an ATM to withdraw money. Through IoT and edge computing, the ATM identifies you and just as you key in your PIN and withdraw cash, it reminds you that this month’s EMI on your house loan has not been paid and that you can avoid penalties if you pay today! Won’t you be pleasantly surprised and thankful to the ATM (literally)! This is one example that illustrates the future possibilities of banking, and this can be made possible through IoT, coupled with intelligent edge computing.
Offering near real-time decisions at the nick of time: By implementing machine learning and cognitive computing, enterprises can automate decision making and drive devices and machines to take prescriptive actions autonomously. This means that a complex network of devices can react in near real time and ensure that minimal accidents happen. Consider the freak accident involving a man who died after carrying an oxygen cylinder into an MRI machine room in January 2018. Due to human error and negligence, the man was allowed into an MRI room with a metal container leading to his tragic death. Such accidents can be prevented with smart devices and networks that are fast, intelligent and reliable. Using a combination of intelligent sensors and scanners, people can be automatically scanned before they enter a room containing an MRI. If the MRI is on, and the person entering has a piece of metal on him/her, a frantic, automated alarm can be raised, and the machine can be switched off automatically too. Such near real-time decisions can save the valuable life of an individual and prevent bad reputations for hospitals as well!
Greater governance, compliance, and security: With an intelligent edge, information collected by devices and sensors need not travel beyond a couple of meters, as the data gets processed and actions get implemented at the ‘edge’ itself.
Thus, as enterprises become IoT-ready, they will also have to deploy edge computing to be able to manage millions of endpoints. This means that they must deploy and manage specific gateways, recruit people and processes to monitor the edge and manage the integration of new devices into edge-computing networks. To me, edge computing is a game changer. What do you have to say about the future of edge computing in connected networks? Let me know.