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Your location: Home > Related Articles > Why is edge computing so important in today’s era?

Why is edge computing so important in today’s era?

Author:QINSUN Released in:2024-01 Click:38

Edge computing is changing the way millions of devices process and transmit data. The explosive growth of Internet connected devices (IoT) and new applications that require real-time computing power continue to drive the development of edge computing systems.

Faster network technologies, such as 5G wireless, enable edge computing systems to accelerate the creation or support of real-time applications, such as video processing and analysis, autonomous vehicle, artificial intelligence and robots.

What is edge computing?

Fundamentally, edge computing enables computing and data storage to be closer to the device that collects data, rather than relying on a central location that may be thousands of miles away. This is done to prevent data (especially real-time data) from encountering latency issues that may affect application performance. In addition, companies can save money by completing processing locally, thereby reducing the amount of data that needs to be processed in centralized or cloud based locations.

The development of edge computing is due to the exponential growth of IoT devices, which connect to the Internet to receive information from the cloud or transfer data back to the cloud. Many IoT devices generate a large amount of data during their operation.

Benefits of edge computing

For many companies, cost savings alone may become the driving force for deploying edge computing architectures. Companies adopting the cloud in many applications may have found that bandwidth costs are higher than they expected.

However, the big benefit of edge computing is more and more the ability to process and store data faster, thus enabling more efficient real-time applications that are critical to companies. Before edge computing, smart phones that scan faces for face recognition will need to run face recognition algorithms through cloud based services, which will take a lot of time to process. With the edge computing model, in view of the increasingly powerful functions of smart phones, this algorithm can be run locally on the edge server or gateway, or even on the smart phone itself. Applications such as virtual reality and augmented reality, autonomous vehicles, smart cities, and even building automation systems require rapid processing and response.

Companies like NVIDIA have realized the need for more processing at the edge, which is why people are seeing new system modules with built-in artificial intelligence capabilities. For example, the company's new module is smaller than credit cards and can be built into smaller devices such as drones, robots, and medical devices. AI algorithms require a lot of processing power, which is why most algorithms run through cloud services. The growth of AI chipsets that can be processed at the edge will allow for better real-time response in applications that require instant computing.

shortcoming

However, like many new technologies, solving one problem may lead to other problems. From a security perspective, edge data can be cumbersome, especially when it is processed by other devices that may not be as secure as centralized or cloud based systems. As the number of IoT devices increases, IT must understand the potential security issues surrounding these devices and ensure that these systems can be protected. This includes ensuring that the data is encrypted and that the correct access control methods or even VPN tunnels are used.

In addition, the requirements of different devices for processing capacity, power, and network connectivity may affect the reliability of edge devices. This makes redundancy and fault transfer management crucial for devices processing data at the edge to ensure correct data transmission and processing in the event of a single node failure.

5G and the Future of edge computing

In the coming years, wireless communication technologies such as 5G and Wi Fi 6 will also affect edge deployment and utilization, enabling unexplored virtualization and automation features such as better vehicle autonomy and migrating workloads to the edge, while making wireless networks more flexible and cost-effective.

With the rise of the Internet of Things and the sudden surplus of data generated by such devices, edge computing has attracted people's attention. However, as IoT technology is still in a relatively early stage, the evolution of IoT devices will also have an impact on the future development of edge computing. An example of this future alternative solution is the development of Micro Modular Data Centers (MMDCs). MMDC is a data center in a box, which places a complete data center in a small mobile system that can be deployed closer to the data - such as in a city or region - to bring computing closer to the data without making it more suitable.

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