Since then, there has been a lot of discussion around edge computing and the Internet of Things (IoT). However, the technology has really come of age now, thanks mainly to the rising interest in artificial intelligence (AI) and, of course, a much-needed fillip from fast 5G networks and powerful mobile processors.
Edge computing is basically a distributed computing framework that moves processing and storage to the edge of the network—that is, as close as possible to the users and sources of data, such as the Internet of Things (IoT) or local edge servers. So, why would someone want to do that? Because, speed matters! Today, everyone wants instant answers and solutions, and the cloud alone cannot handle this crowd. This is true not just for futuristic or high-stake applications like self-driving cars and military operations but also for common ones like shopping and marketing campaigns.
Delays are costly
From industries to automobiles and traffic signals, every device is racing to become smart. Relying solely on the cloud to accommodate this exponential growth of users would result in increased latency—an intolerable outcome. And, it can be more serious than a customer getting irritated by a delay in connecting to a local restaurant’s menu. A millisecond’s delay in decision-making in an autonomous car could cause an accident, or lack of connectivity in a surveillance drone could mean not spotting an impending missile attack! In today’s scenario, reducing latency is of utmost importance. On-device processing, in tandem with the cloud and on-premise data centres, can handle this situation very well. It also brings with it other perks like creating personalised customer experiences and improved security.
This story is from the September 2023 edition of Electronics For You.
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This story is from the September 2023 edition of Electronics For You.
Start your 7-day Magzter GOLD free trial to access thousands of curated premium stories, and 9,000+ magazines and newspapers.
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