Edge Computing – The right choice for a real-time IoT solution

In recent years, edge computing has become one of the biggest trends in IoT. If cloud computing is likened to a big data processing center located at the core of the system, edge computing is right at the edge, helping to optimize the system by simple data processing at the edge of the network.

With edge computing, time-sensitive data can be processed at the point of origin, intermediate servers can process data close to the source geographic location, edge application services significantly reduce the amount of data that needs to be moved, reducing transmission costs.

1. What is edge computing?

Edge computing is a network of centers that process and store data locally before it is sent to the Data Center or to the clouds. It optimizes transmission systems to avoid interruptions or delays in sending and receiving data. Edge computing is armed to optimize cloud computing by processing data at the edge of the network

2. How does edge computing work?

For edge computing, data sent from sensors or other data collection devices will be processed and responded to at the nearest device or node without the need to send data to the cloud center and wait for a response.

Architectural model of edge computing

This data can be processed locally at the device, so the response time is very good, creating momentum for the development of a real-time system.

3. Advantages of edge computing

Edge computing allows to clarify the extent of computing resources to optimize processing and offers many advantages:

• Fast data response speed, processed at the origin of data by local processor • Edge application services significantly reduce the amount of data to be transferred. • Eliminate bottlenecks in data transmission and data conversion calculations • High reliability. • Cost efficiency. • Unlimited scalability and high security.

An overview of the differences between edge computing and cloud computing

Cloud computing Edge computing
Working method Devices send data to the cloud and wait for a response. The data from the collection device can be processed and responded locally without sending it to the cloud.
Response time Maybe up to 1 second In microseconds
Real-time IoT Not suitable Suitable
Architecture Complex data analysis, long-term data storage. Basic data analysis, short-term data storage.

Thus, the application of edge computing to data processing and transmission is especially important, it supports faster processing, reduces the load on application services, and reduces latency in data transmission to the cloud network and many other outstanding features.

4. Applications of edge computing

Edge computing is an important infrastructure and an inevitable trend for the development of tourism, transportation, energy, healthcare, banking, etc. That’s because of the potential of edge computing combined with other technologies such as artificial intelligence, cloud, and 5G networks to help optimize network infrastructure and improve customer experience.

Prominent applications of edge computing:

  • Education: increase uptime and reduce support costs.
  • Retail industry: improve customer experience.
  • Digital hospital: improve care and response.
  • Manufacturing industry: improve the performance
  • Reduce the amount of data exchanged with icloud servers in virtual reality (VR), augmented reality (AR), mixed reality (MX) devices.
  • Application in intelligent transportation system.
Application in intelligent transportation
  • In the field of UPS & power storage, with its compact, flexible design and the ability to meet the specific requirements of edge computing and small data centers (limited installation and operation space) , INVT UPS is the first choice of customers.

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