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Exploring Edge Computing: From Core Principles to Edge Computers
Release Time:2023/12/29 Number Of Clicks:358

Exploring Edge Computing: From Core Principles to Edge Computers

Edge computing is a distributed computing architecture that allows fast and accurate analysis and processing of data at the source to ensure immediate and rapid response. This contrasts sharply with the centralized computing strategy of the past, where data relied entirely on the cloud or a central data center. With the rise of AI technology and the proliferation of smart devices, the scale and complexity of data are rapidly increasing. Especially in fields such as smart warehousing, vision-oriented manufacturing processes, or traffic management in smart cities, data transmission needs often exceed the capacity of the network. 

Coupled with the increasing technological advancement in industrial computers, cameras, mobile terminals, sensors, and various Internet of Things (IoT) devices, the speed of data generation and collection continues to increase. Relying solely on central data centers can no longer meet existing needs, so now, edge computing has progressed from a simple trend to the best solution.

Edge Computing Architecture

Typical edge computing architecture can be divided into three layers: the device layer for data collection, the edge layer for real-time data processing, and the cloud layer responsible for secure storage and deep analysis.

Device Layer:This layer covers various types of IoT devices, each collecting and monitoring data through built-in sensors. For example, medical instruments in hospitals focus on monitoring patients’ vital signs, while autonomous vehicles gather data on road conditions and the dynamics of other vehicles.

Edge Layer:As the core of edge computing, the edge layer is located closest to the source of data generation and has a wider distribution than traditional cloud servers. It can perform real-time data processing and analysis, significantly reducing latency. If data requires deeper analysis, it is uploaded to the cloud layer for further processing.

Cloud Layer :Although cloud computing addresses bottlenecks and latency issues in cloud computing, in a complete edge computing architecture, cloud computing and edge computing complement each other. When the edge layer determines that some data requires more detailed analysis, it uploads this data to the cloud layer for deeper computation and storage.

Five Advantages of Edge Computing

Rapid Response and Improved Efficiency:
In highly automated industries such as factory production lines, real-time data transmission and processing are crucial. Real-time monitoring and corrective actions in the event of machine anomalies significantly reduce production downtime and potential risks.

Enhanced Data Security:

Edge computing processes and stores most data on-site, encrypting necessary data before transmitting it back to central data centers, ensuring data security.

Leap in Productivity:
Enterprises can improve operational efficiency through real-time data feedback. Combined with artificial intelligence and machine learning, edge computing can perform in-depth analysis of business data, helping companies identify areas for improvement and make rapid decisions.

Remote Data Collection:
Traditional data collection methods often encounter difficulties in remote areas with unstable network connections or limited bandwidth, such as offshore oil fields or vessels. Edge computing brings computing and storage capabilities directly to these remote locations, ensuring smooth data collection and transmission.

Cost Optimization:
Transmitting large amounts of data consumes a significant amount of bandwidth and comes with relatively high setup costs. However, the edge computing architecture allows selective transmission of essential core data, reducing overall setup expenses.

The Core of the Edge Layer - Edge Computer 

As the core system component of the edge layer, the edge computer is responsible for processing and analyzing data collected from the device layer. To execute tasks quickly and robustly, edge computers require the following features.

High Durability:

Because edge computers are located close to the device layer, they must maintain superior reliability in ever-changing and harsh environments. This becomes especially important when these devices are exposed to extreme climates or challenging environments. Fanless design ensures stability even in polluted, dusty, or humid environments. Additionally, shock resistance and vibration tolerance are essential when operating in high-vibration environments.

Outstanding Performance:

Edge computers need to be able to efficiently analyze and store data from the device layer, making performance a critical factor. The increasingly complex data analysis challenges are also accelerating with the rapid evolution of AI technology. To meet these demands, edge AI computers have emerged. In addition to supporting multi-core CPUs, they also feature GPUs specifically designed for real-time image processing.

Rich I/O, Connectivity, and Storage:
To ensure direct connectivity with various devices, edge computers need a selection of commonly used I/O interfaces. For connectivity, options such as WiFi, 4G, 5G, GNSS, and Bluetooth, in addition to wired transmission, ensure seamless connections in different field scenarios. Furthermore, considering the vast amount of data collected from the device layer, edge computers also support options for large-capacity or high-speed storage.

Industrial-grade Protections:
Edge computers are often deployed in remote or harsh environments. Therefore, having industrial-grade protection features becomes crucial. Features like wide voltage support, ESD protection, surge protection, and EMC protection ensure efficient and stable operation under various conditions.

Flexible Installation Options:
Edge computers are frequently deployed in space-constrained areas and various other locations, so a variety of installation options is necessary. Whether it's wall mounting, VESA mounting, DIN rail mounting, or panel mounting, these options offer users multiple deployment choices to meet different application needs.

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