Edge Computing

What is Edge Computing?

Edge computing is an open and distributed platform that seamlessly integrates key functionalities of networking, computing, storage, and applications. It offers intelligence services at the network edge, specifically in proximity to devices or data sources. In essence, edge computing involves analyzing data directly from terminals located at or near the point of data generation, eliminating the necessity of transmitting data to a cloud-based data processing center.

The Significance of Cloud Computing

With the rapid advancement of IoT technology, there is an increasing interconnection of everyday objects with independent functionalities. IoT facilitates the networking of numerous industry terminals, leading to the acceleration of digital transformation across various sectors.

Nevertheless, IoT represents a vast and intricate system, with application scenarios differing across industries. According to third-party analysis organizations, it is projected that by 2025, there will be over 100 billion devices connected to the Internet, resulting in a data volume of around 300 ZB. In the traditional data processing approach, all collected data needs to be transmitted to the cloud computing platform for analysis. However, this poses significant challenges for the cloud computing platform, including high network latency, the need to connect a multitude of devices, difficulties in processing massive data, bandwidth limitations, and high power consumption.

This is where edge computing plays a pivotal role. Edge computing is a distributed and open platform that integrates the essential capabilities of networking, computing, storage, and applications. It provides intelligent services at the network edge, in close proximity to devices or data sources. In simple terms, edge computing directly analyzes data collected from terminals located at or near the device or network where the data is generated. By doing so, there is no longer a requirement to transmit all data to a centralized cloud data processing center.

Edge Computing and Cloud Computing

Edge computing and cloud computing are two concepts that exist in relation to each other. Cloud computing involves uploading data to resource-intensive cloud data centers or servers for processing, requiring all data access requests to be transmitted to the cloud.

However, the explosive growth of data driven by IoT exacerbates the limitations of cloud computing:

• Cloud computing struggles to efficiently handle the increasingly massive volumes and diverse sources of data. The integration of the Internet with various industries, especially with the widespread adoption of IoT, has led to a significant surge in demand for computing power. This surpasses the processing capabilities of traditional cloud computing architectures.

• Cloud computing cannot support real-time data processing. In the traditional cloud computing architecture, IoT devices collect data, which is then transmitted to remote cloud computing clusters located in data centers. The clusters process the data and send back the results. This process results in significant response times. However, emerging applications such as autonomous driving and smart mining have stringent requirements for real-time processing, making cloud computing unsuitable for these scenarios.

These issues can be somewhat resolved via edge computing. In edge computing, data generated by IoT devices is not transmitted to remote cloud data centers for processing. Instead, the data is analyzed and processed at the network edge, which is more efficient and secure compared to cloud computing.

Operational Mechanism of Edge Computing

The architecture of edge computing enables data processing near the terminals, eliminating the need to transmit data to a centralized cloud computing center. Here is how edge computing works:

• Terminal: The terminal layer consists of various IoT devices like sensors, RFID tags, cameras, and smartphones. These devices collect raw data and transmit it for further processing. The focus of IoT devices at this layer is on sensing capabilities rather than computing capabilities.

• Edge computing node: Edge computing nodes are responsible for providing basic services by deploying computing and storage resources at the network edge. These nodes process data locally, reducing latency and enabling faster response times.

• Network node: The network node transfers relevant and valuable data obtained from edge computing nodes to cloud computing nodes for analysis and further processing. This ensures that critical data is efficiently utilized for insights and decision-making.

• Cloud computing node: Cloud computing nodes store the data reported by the edge computing layer. They handle analysis tasks and comprehensive processing that go beyond the capabilities of edge computing nodes. Cloud computing nodes dynamically adjust deployment strategies and algorithms at the edge computing layer based on the distribution of network resources.

Typical Edge Computing Applications

Edge computing is particularly well-suited for the IoT field due to its ability to process data in real-time and deliver faster responses. One key application of edge computing in IoT is the deployment of EC-IoT gateways, which possess edge computing capabilities. These gateways are strategically placed near network edge nodes and offer services like device management and control. By addressing the "last mile" problem in IoT communication, EC-IoT gateways enable smart connectivity and efficient management of IoT devices.

Edge computing is specifically designed to cater to the needs of the industrial IoT field. It provides extensive support for various industrial protocols and IoT interfaces, enabling seamless device connections in diverse industries. The open capabilities of edge computing, combined with its cloud management architecture, effectively fulfill the intelligent data processing requirements of different industries：

• Connectivity: Edge computing gateways, known as EC-IoT gateways, facilitate connectivity by offering a wide range of IoT interfaces. These interfaces include IP-based Power-line Communication (PLC), radio frequency (RF), RS485, and RS232. By supporting such diverse interfaces, EC-IoT gateways enable the seamless connection of a large number of sensors and terminals to IoT networks.

• Cloud-based management: Cloud-based management is a key feature of edge computing. Through the utilization of cloud computing technologies, customers can implement centralized management of edge IoT resources, including networks, devices, containers, and applications. This centralized management approach simplifies operations and allows for efficient monitoring and control. Moreover, the platform offers open northbound application programming interfaces (APIs), enabling easy integration with other industry application systems and promoting flexibility.

• Customization of industry applications: The IoT platform emphasizes the customization of industry applications. It provides standard open APIs that can be integrated with industry-specific application systems offered by partners. This adaptability across industries allows for extensive customization and tailoring of the IoT platform to meet the specific requirements of different industries.