Edge computing refers to using nearby data processing capabilities at the edge of the network to move the traditional centralized data processing process closer to the user. This is like a “disconnected” switch or router, allowing data to reach its destination faster.
The edge computing gateway can also be understood as an intermediate node, which moves the traditional centralized computing process to the network that is closer to the user and has the largest bandwidth, effectively improving the enterprise’s production efficiency and response speed. Edge computing gateways are an important interface for edge devices to connect to the cloud, collect and process data and application services.
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Since the end-to-end communication bandwidth of the device is limited, there will be a certain degree of delay limitation when transmitting data. During the data transmission process, it is often affected by network fluctuations, traffic and delays, resulting in transmission lags, high delays, low efficiency and other problems, which affects the business experience. After combining cloud computing and edge computing technology, end-to-end connections can be established closer to the user side and closer to the network side to solve problems encountered during data transmission.
The characteristics of edge computing gateways include the following aspects:
1. Data collection and data processing
Because the traditional data processing method is often concentrated on the server, the efficiency of this method will be relatively low and the data processing time will also become longer. Edge computing can solve this problem and bring network devices closer to users. Edge servers are used to collect, analyze and process user-side data, and forward the data to edge computing gateways when users are close, allowing them to respond directly to user requests.
2. Reduce network bandwidth
Edge computing devices can be deployed near users and can reduce network bandwidth. In many IoT devices, data processing needs to be completed closer to the network, thus reducing the bandwidth of data transmission. For example, an image file generated by a user can be quickly distributed at the edge of the network, reducing waiting time and traffic, thereby reducing bandwidth costs.
3. Reduce latency
Traditional data centers have many technical bottlenecks due to their large scale and high cost. The edge computing architecture can solve this problem very well. The massive data originally to be processed by the cloud is classified and sorted by the edge device and then forwarded to the cloud for processing, avoiding problems such as delays. Therefore, in terms of data transmission, edge computing can effectively reduce latency and improve efficiency compared to traditional data centers.
4. Enhance data security
Edge computing solves the security problems of cloud data storage through distributed storage, load balancing, security policies and other means. At the same time, it disperses massive cloud data to edge computing nodes to avoid excessive network traffic from affecting user experience.
5. Realize network intelligence and improve network stability
Edge computing gateways can process data nearby without affecting the network, improving data transmission timeliness and improving data collection and analysis capabilities.
Edge computing gateways have a wide range of application scenarios and can be used in finance, logistics, transportation and other industries: they can be used to protect key data, ensure data security, and improve business experience. The application of edge computing is to deploy some core applications on the network closest to the user, thereby improving the overall network stability and reliability; at the same time, it can also realize the rapid collection and analysis and processing of key data, thereby improving the business processing speed and also Improved operational efficiency.