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Demystifying Edge vs. Cloud Computing

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Demystifying Edge vs. Cloud Computing

“Edge computing is likely to work in tandem with cloud computing — not replacing it.''

· IoT Zone ·
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Around 10 percent of enterprise-generated data is created and processed outside a traditional centralized data center or cloud. Gartner predicts that by 2022, this figure will reach 75 percent.

The very existence of cloud took the entire world by storm, and in the process, it proved that it was more than just hoopla. It’s still a big deal, and we have seen an exponential growth of SaaS applications over the years. Since the inception of artificial intelligence (AI), the industry is having a paradigm shift from cloud to something known as ‘edge.’ Moreover, with the Internet of things (IoT) bemusing the digital space, edge computing is gaining domain authority. There have been various speculations by the industry pundits that edge computing is going to edge out cloud computing. Well, the short answer is: no. But a more complex answer is that with the growing data crunch and quick adoption of AI, the cloud may not always be a viable option!

Difference Between Cloud and Edge Computing

Cloud computing is basically using a remote server for management, storage, and processing of the data. It’s like a centralized architecture that can be accessed from anywhere, anytime. In cloud computing, the data is sent to the cloud and located at a great distance from the point of origin. The cloud then processes this action and the data is pulled down from the cloud by the customers as and when needed. Because these data processing units are located off-shore, issues like the freshness of the data, latency, and accuracy of data are often impacted when using the cloud computing architecture.

Edge computing is often referred to as "on-premise." A computing topology in which information processing power, data collection, and delivery are moved closer to the edge of the device. Instead of housing processing power in a cloud or a centralized data center, data processing occurs in multiple small data centers located at or near the source. The main purpose of edge computing is to push the data as close to the actual device as possible, thus reducing traffic and latency.

Will Edge Computing Replace Cloud Computing?

The growth of connected devices is predicted to increase to 22Bn by 2025 against 7Bn in 2018 as per the estimates from IoT analytics. Data is inextricably linked to the exponential growth of these connected devices.

The reason why businesses are preferring edge over the cloud is that of reduced latency and edge is more cost-effective. Businesses want to move the processing and storage close to the application. When the data processing can be made available close to the device, it increases the reliability of the data collected and ensures that there is no delay in information as it switches between routers, servers, and firewall. Whereas, with the cloud, it is the opposite. The data is pushed and stored in the cloud and then pulled back when needed. This works well for images, videos, music, etc., but do you think that this will also work for real-time scenarios in manufacturing units or for an autonomous car per se?

Source: External

The main advantage of edge computing is speed. The IoT concept envisages quick responses for data processing like in the case of self-driving or autonomous cars. To stay safe on the roads, autonomous cars need to collect and process massive amounts of data like following the lane rules, stopping at red lights, identifying pedestrians, etc. All of this requires cars to process tons of data in real-time every millisecond of the ride. With so much to be processed quickly, these cars cannot rely on cloud servers where the data is uploaded in the server, processed, and then waiting for the results. Cloud services can be pretty fast but not fast enough to respond in real-time to the immediate dangers. Whereas, edge computing can do all these jobs in real-time. Instead of using the cloud for doing the processing off-shore, the data can be collected and stored in the cloud. The vehicle manufacturers can use the data they have gleaned to offer smoother and safer rides.

Similarly, in industrial IoT, there are scenarios where it is sometimes necessary to manage devices without a proper network bandwidth; this eliminates the opportunity to apply cloud computing. In such scenarios, edge computing is the optimal solution. Here, I can list many IoT use cases that prove that edge has the domain authority over the cloud, but they cannot replace each other. Edge computing just moves the processing power and storage closer to the application.

When it comes to edge and cloud computing, they are not necessarily in competition with each other. Instead, the two technologies can complement each other. It is up to the businesses to analyze their unique needs and figure out the right balance between how much processing should be done on the cloud and how much should be done on the edge devices.

“Edge computing is likely to work in tandem with cloud computing — not replacing it."

See how CEP engines, stream processing engines, flow based programming engines and other popular rule-based technologies perform against seven IoT-specific criteria.

Topics:
edge computing ,cloud computing ,internet of things ,cloud ,saas adoption ,iot ,ai ,data

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