When 5G began rolling out, so began a lot of conversations using newer technology terms one of which being edge computing. But what is edge computing and how can it impact your business?
Before data computing moved to the cloud, data was typically transmitted and stored on site. In the case of large operations, those enterprises generally had private data centers, while smaller organizations leveraged server and networking hardware to build their IT operations.
With the introduction of the cloud, organizations can host data on cloud servers, which is essentially using that cloud service provider’s hardware and infrastructure. The ability to essentially move away from physical infrastructure allowed organizations to scale and grow IT operations without the same manpower or financial investments.
Now, 5G with its low latency and high bandwidth is making it possible to move data computing from the cloud closer to the end user, depending on the use case.
With massive amount of data being transmitted and processed by organizations, sometimes it’s not always viable to have data going to a central location. Gartner predicted that by 2025, 75 percent of enterprise data will be created and processed at the edge instead of the cloud.
And many hyperscalers – large industry leaders offering cloud services -- have been working to create offers in edge computing.
Edge computing has many benefits as the infrastructure to support distributed computing is closer to the data source:
Greater bandwidth: When millions of devices are connected to the internet, data processing requirements are massive. Local area networks (LAN) or wide areas networks (WAN) only have so much capacity for data transmission, and the same is true for cellular networks. Competition for bandwidth can create network congestion and lags. For mission-critical communications, like in autonomous vehicles or robotics, having more bandwidth dedicated to that individual operation will yield more consistency and reliability.
Latency: The speed with which data is transmitted and computed has the potential to be lowered with edge computing. A centralized cloud location might have too high latency for those mission-critical communications.
Accessibility: Some use cases for edge computing rely on the accessibility of being able to transmit and process data on site. When connectivity is unreliable or bandwidth is restricted because of environmental factors – such as on oil rigs – or because of remote locations, such as the desert – being able to leverage edge computing or even edge devices is crucial to those technologies.
Many of the use cases for edge computing rely on those benefits of bandwidth, latency, and accessibility across many verticals that are becoming more and more reliant on digital operations.
Healthcare: The market landscape for connected healthcare is anticipated to be valued at $446 billion by 2028, a sharp increase from $71.84 billion in 2020. IoT in healthcare is expected to connect medical sensors and devices to the internet for use cases in remote patient monitoring and decentralized clinical trials, among others. With so many connected devices, and in those use cases of mission-critical data transmission – such as robotics or implanted devices – dedicated bandwidth and latency will be highly important.
Manufacturing: With a shift to greater digital approaches to running production lines, predicting equipment maintenance, and through the value chain, manufacturing is an area that has the ability to produce a significant amount of data, which edge computing can help manage. With mission-critical robotics, automated guided vehicles (AGVs) and artificial intelligence (AI) in workplace safety, the latency provided through edge computing is beneficial.
Fleet and Auto: Whether in consumer or enterprise applications, autonomous vehicles will compute large packets of data that need to be transmitted rapidly, making edge computing a relevant choice.
Enterprise: Enterprise applications of edge computing is a catchall and can refer to many different use cases. Enterprise use of edge computing comes down mostly to the benefits of the edge and the technologies it can support. For example, edge AI can be leveraged across many verticals. AI has the ability run faster and more reliable coverage when using the high speed and low latency of edge computing.
Migrating to an edge computing solution, or even a partial edge computing solution, can be complex. Partnering with a provider with a deep knowledge of connectivity and technology infrastructure can mitigate challenges that might arise in the process. Want to learn more? Reach out – we’d love to talk!
Check out our on-demand webinar, “AIoT: Analyzing Data on the Edge”, to learn more.
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