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Edge Computing: Igniting the Innovation Revolution Across Industries – ReadWrite

In the pandemic’s wake, enterprises rapidly relocated their workloads to the cloud to drive continued productivity and ensure business continuity. But is the cloud always the answer? Not always.

Internet of Things (IoT) devices — now 10 billion worldwide — generate tremendous amounts of information in real-time and suffer lackluster performance if they must send the data back and forth to the cloud, resulting in transmission and compute latency, decreased agility, and inflated costs.

This prompted enterprise IT teams to leverage the Edge, a distributed digital architecture that moves computation, storage, and network services near the end-users to boost the quality of app performance.

What constitutes the Edge?

Think of it in two ways. First, there’s the far edge, where enterprise IT teams conduct edge computing on-premise, which can range from brick-and-mortar retail stores to autonomous cars and beyond. These disparate locales all share a common denominator: They’re performing computations at the end-user’s location, where the data is originally collected.

So what’s the real benefit of edge computing? By localizing the data, it doesn’t need to travel, which speeds data up processing, lowers latency, and increases network bandwidth savings. Edge computing is quickly becoming a must-have staple for enterprise IT teams.

In fact, in 2022, more than 40% of companies’ cloud rollouts will integrate edge computing, with the global market forecasted to earn nearly $250 billion in 2024.

 What about near-edge and multi-access edge computing?

Alternately, there’s the near edge, which provides multi-access edge computing, a market poised to generate $23 billion by 2028.

MEC enables enterprises to harness real-time cloud services powered off-premises at the service provider’s network edge — occurring at base stations, telco data centers, or points of presence (PoPs). Still residing extremely close to end-users. This results in improved data performance, faster processing speeds, and enhanced storage capabilities.

Far edge and the near edge computing provide the same service

Definitions aside, both the far edge and the near edge provide the same service: Secure, reliable, and performant network connectivity. This can only be achieved through secure access service edge (SASE), which delivers SD-WAN and security-as-a-service to both near and far-edge sites via a global network of PoPs.

Here’s a closer look at how edge computing, SASE, and MEC are transforming end-user data collection, processing, analysis, and storage across industries.

Harnessing the power of edge computing

By 2025, as connectivity requirements scale across industries, 30% of all data will be created and collected in real-time. To enable a real-time response, this data must be processed on premises at the far edge, which positions resources, including storage, computing, and networking, as near as possible to end-users.

This helps customer networks substantially lessen latency, accelerate data processing, and increase bandwidth savings.

Who stands to gain from edge computing?

Everyone — from manufacturing, farming, and healthcare to network optimization, workplace safety, and retail — the possibilities are practically limitless.

In addition to providing solutions for framework issues like bandwidth limitations and network congestion, the implementation of edge computing gives autonomy where reliable connectivity may be hard to come by, plus data sovereignty and security that allow sensitive data to be processed and secured locally via encryption or other methods before it’s sent to the cloud.

Computing for Augmented Reality

Imagine you’re a retail store owner. By offering interactive digital content, you can enhance your customers’ experiences in countless ways. For example, edge computing helps run augmented reality-powered shopping apps like smart mirrors that require real-time human feedback.

And what if you’re riding in an autonomous car? Only through edge computing can your vehicle ingest, process, and analyze data from numerous sources, spanning car sensors to satellite data and much more. This information must be aggregated and processed in real-time, empowering your car’s artificial intelligence to make split-second driving decisions and keeping you safe.

SASE provides cheaper, more flexible solutions to protect data

With the number of monthly active users for mobile augmented reality apps projected to reach 1.9 billion in 2022, combined with the continued popularity of remote work and increasingly complex security threats around the world, enterprises are looking for solutions to securely connect users to business and entertainment resources and applications, no matter what device is being used or where the user is connecting from.

Though effective, SD-WAN is designed to connect branches and specific home workers — inefficient with the growing amount of remote devices and services outside those branches. Enter SASE, which combines the network performance benefits of SD-WAN with a more efficient method of delivering on-demand security services anywhere, similar to other cloud services.

As networks send and access real-time data from various cloud locations, SASE ensures on-demand connectivity and automates the process of protecting both data and end-user devices. By crafting a global network of PoPs that serve as a stepping stone to a variety of cloud services, each PoP can apply the full suite of enterprise security functions, regardless of when or where users, devices, or applications connect.

SASE technology is quickly becoming a core asset for enterprises looking to boost their network security

SASE tech inherently reduces the number of vendors IT teams require, which is cheaper and cuts down on technological complexity. Further, SASE provides better performance for companies that frequently use real-time latency-sensitive collaboration tools thanks to its ability to route through multiple PoPs.

The SASE distributed architecture is optimal for remote work, making it easy for IT to perform security functions for the end user.

As with any new technology, the marketplace is still figuring out what an effective SASE solution looks like. Innovators must continue striving for innovations to provide flexible solutions that don’t compromise scalability for simplicity.

MEC: Revving up data speeds and reducing latency

By 2025, an astounding 175 zettabytes of data will be created annually — with enterprises producing 60% of it. How much data is 175 zettabytes? Better clear your schedule — you’d need 1.8 billion years to download it all.

MEC will help you prepare for this massive shift in big data.

MEC tackles tremendous amounts of information in real-time, performing data analysis, processing, and storage. Instead of running these tasks in distant clouds, they’re performed in base stations, telco data centers, or PoPs at the near edge — via radio access networks — nearby your network, with SD-WAN providing enhanced connectivity and security.

MEC powers ultra-low latency

How does this change the game? MEC powers ultra-low latency, lightning-fast data transmission, and enhanced quality of experience (QoE) for your customers. Additionally, it radically reduces the traffic that’s offloaded to the core network or backend server, freeing these assets up for other business-critical needs.

Like edge computing, MEC supports infinite use cases across industries. For example, manufacturers will use MEC to support agile smart factories. Using MEC, even the tiniest faults or defects can be instantly detected via video and analyzed, empowering engineers to ensure minor issues don’t snowball into major problems.

Law enforcement sees the benefit of MEC too.

Equipped with dash cams in their squad cars and wearing body cameras, British police have struggled to offload all their imagery data to a central place where it can be analyzed and stored. To address this, inside the trunks of their police cruisers, they’ve installed ruggedized UCB-style devices, a video processing unit (VPU), an SD-WAN Edge device, a Wi-Fi card, and dual LTE connections.

So, as officers exited their cruisers, their cameras broadcast over Wi-Fi to a recorder in the trunk of their car. After the VPU processes the data, it’s uploaded over the dual LTE — using SD-WAN technology to improve the quality of connectivity — to a base station at the near edge for video post-processing, analysis, and storage.

Conclusion

To enhance app performance, enterprises around the world are turning to the Edge. At the far edge, data is processed where it’s collected in real-time and extremely close to users, radically reducing latency.

At the near edge, MEC does the heavy lifting, handling volumes of data in real-time and performing data processing and analysis at warp speed, delivering improved end-user QoE. What’s the endgame for IT teams?

By reducing their reliance on the cloud, they can speed data transmission, boost agility, and reduce costs — supporting next-generation innovations that are only limited by imagination.

Featured Image Credit: Photo by Valdemaras D; Pexels; Thank you!

Marilyn Basanta

Sn Director, Product Management, Edge Computing, VMware, Inc.

Marilyn Basanta is the Senior Director of Product Management for VMware’s Edge Compute product line. Formerly a software engineer for IBM, she came to VMware as a solutions architect and built out E2E vertical solutions. She moved into product management and launched VMware TestDrive as part of the End User Computing business unit. Now at VMware for over a decade, she is focused on Edge and is responsible for VMware’s Edge Compute Stack.

This UrIoTNews article is syndicated fromGoogle News

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