Before we get to edge computing, let's talk about the "octopus," one of the smartest creatures on Earth. As invertebrates, they have a huge number of neurons, but 60% are distributed on their legs, and the remaining 40% are on their brain. With this distributed computing of “multiple cerebellums plus one brain“, they are nimble and fast.

Just like Octopus's distributed computing, edge computing collects data and processes at the edge as well.

Ⅰ. What Is Edge Computing?

Edge Computing Definition

Edge computing is a type of network edge detection that is physically close to the source of data. It integrates the open platform of network, computing, storage and application core capabilities, and provides the computing mode of edge intelligent services nearby. To put it simply, edge computing is to analyze the data collected from the terminal directly in the local device or network near the data generation, without transferring the data to the cloud data processing center.

The location where the edge computation occurs is called the edge node. It can be any node with computing resources and network resources between the source of data generation and the cloud center. For example, the phone is the edge point between the person and the center of the cloud. In an ideal environment, edge computing refers to the analysis and processing of data near the source of data generation, without the flow of data, thereby reducing network traffic and response time.

Why Do We Need It?

With the increasing number of IoT devices, the data generated at the edge of the network is gradually increasing. If the data can be processed and analyzed at the edge nodes of the network, this computational model will be more efficient.

A.Cloud Services Driven

The cloud center has powerful processing performance and can handle massive amounts of data. However, due to the limited bandwidth of the network, it takes a certain amount of time to transmit massive data to the cloud center and to process the data in the cloud center. This increases request response times, resulting in a poor user experience.

B.IoT Driven

The rapid development of Internet of Things technology makes common objects interconnected. Various industries are trying to use IoT technology to achieve rapid digital transformation. As a result, more and more industry terminal equipment is connected through the network.

However, as a huge and complex system, the Internet of Things has different application scenarios in different industries. According to third-party analysis, by 2025, there will be more than 100 billion terminal devices connected to the Internet, and the amount of terminal data will reach 300ZB. For such a large amount of data, if it is carried out in accordance with traditional data processing methods, all the data obtained needs to be uploaded to the cloud computing platform for analysis. The cloud computing platform will face the challenges of high network delay, massive device access, difficult processing of massive data, insufficient bandwidth and high power consumption. In order to solve these problems, edge computing technology comes into being.

Edge Computing VS Cloud Computing

We are all familiar with cloud computing, which has huge computing power, massive storage capacity, and various applications can be built through different software tools. Many of the apps we use essentially rely on various cloud computing technologies, such as live video platforms and e-commerce platforms. Edge computing is derived from cloud computing, which is closer to the device side and has the ability to react quickly. However, it cannot cope with the work environment that requires a lot of computing and storage.

The concept of edge computing is relative to cloud computing. The processing method of cloud computing is to upload all data to the cloud data center or server where computing resources are concentrated for processing, and any request to access the information must be sent to the cloud for processing. In the case of the explosion of Internet of Things data, the drawbacks of cloud computing have gradually been exposed.

First, cloud computing cannot meet the demands of explosive mass data processing. With the integration of the Internet and various industries, especially after the popularization of the Internet of Things technology, the demand for computing has exploded. The traditional cloud computing architecture will not be able to meet such a huge computing demand.

Secondly, cloud computing cannot meet the demands of real-time data processing. In the traditional cloud computing mode, after the Internet of Things data is collected by the terminal, it needs to be transmitted to the cloud computing center, and then the result is returned after cluster calculation. This process is bound to result in a long response time. However, some emerging application scenarios, such as unmanned driving and smart mining, require fast and high-speed response times, and relying on cloud computing can no longer meet realistic needs.

The emergence of edge computing can solve these problems encountered by cloud computing to a certain extent. As shown in the figure below, the data generated by the iot terminal equipment does not need to be transmitted to a distant cloud data center for processing, but to complete data analysis and processing at the edge of the network nearby. It is more efficient and secure than cloud computing.

The Differences Between Edge and Cloud Computing

Ⅱ. What Is a Gateway In Edge Computing?

In edge computing, a gateway is a device that connects edge devices, such as sensors or iot devices, to a wider network or cloud. It acts as a bridge between local edge networks and centralized data centers, managing data flow, processing local data, and ensuring secure communication. Gateways can perform tasks such as data aggregation, filtering, encryption, and protocol transformation, reducing latency and bandwidth requirements for data transmission, and enabling faster and more efficient processing at the network edge.

Typical Characteristics Edge Computing Gateways

• Multiple Connection Options: Support Ethernet, 4G LTE, Wi-Fi and other connection methods.
• Industrial Grade Design: Suitable for industrial environments, usually with a robust housing and high anti-interference capability.
• Security: Supports multiple VPN technologies, such as IPsec VPN and OPEN VPN, to ensure the security of data transmission.
• Programmability: Support Python programming, allowing users to customize development according to specific needs.
• Protocol Support: Support a variety of industrial protocols, such as Modbus RTU, Modbus TCP, Ether Net/IP, OPC UA, etc. It is suitable for various industrial application scenarios.

Ⅲ. InHand Networks Edge Computing Solutions

InHand Networks offers full range of Edge computing Gateways. It mainly involves two serials, like below shows.

IG Series:

EC Series:

Conclusion

In this article, we have gained some insight into edge computing. Processing data at edge nodes can improve response speed, reduce bandwidth, and protect the privacy of user data. At the same time, we also introduced the edge computing products of InHand Networks. If you want to know more about edge computing devices or need to purchase related products, please feel free to contact us.

Phone: +1 (703) 348-2988 (US) 010-84170010 (CN)
Email: support@inhandgo.com
Website: https://inhandgo.com/