How Edge Computing Transforms Business: Key Trends and Benefits

In the wave of digital transformation, edge computing is gradually becoming the core of enterprise technology strategy. The concept of edge computing originated from the development stage of cloud computing, which aims to transfer data processing from the central data centre to the edge of the network closer to the source of data generation. In this way, edge computing can reduce the delay of data transmission and improve real-time processing capabilities. It is particularly suitable for application scenarios with extremely high speed requirements such as the Internet of Things and autonomous driving.

The importance of edge computing is becoming increasingly prominent, mainly due to the sharp increase in data volume and the need for instant response. In the traditional cloud computing model, all data needs to be transmitted to a remote data centre for processing, which is inefficient when faced with large amounts of data and low latency requirements. Edge computing reduces latency and bandwidth consumption by processing data locally, while improving data security, and is therefore becoming a key technology in the digital transformation of enterprises.

Key Trends in Edge Computing Development

Key trends not only reflect the current development direction of edge computing technology, but also provide enterprises with new ideas and solutions in the process of digital transformation.

Trend 1: Popularisation of 5G

• The popularity of 5G technology provides strong infrastructure support for edge computing. The low latency, high bandwidth and wide coverage of 5G networks make it possible to process data at the edge of the network. For application scenarios that require real-time response and high availability, such as autonomous driving, augmented reality (AR), virtual reality (VR), etc., the combination of 5G and edge computing is the key to implementing these technologies.

• Enterprises can use 5G networks to distribute computing power to the edge nodes of the network, thereby reducing the load on the core network and improving the agility of services and user experience.

Trend 2: Growth of the Internet of Things (IoT)

• The booming development of the Internet of Things has driven the application demand for edge computing. Hundreds of millions of IoT devices generate massive amounts of unstructured data, and traditional centralised cloud computing architectures can no longer meet the low-latency processing requirements of this data. By processing IoT data at edge nodes, enterprises can not only reduce bandwidth and storage costs, but also reduce data transmission delays and improve the real-time and reliability of business.

• Edge computing provides the IoT ecosystem with greater computing power and flexibility, enabling enterprises to achieve more intelligent and automated operations.

Trend 3: Integration of AI and Machine Learning

• The deep integration of edge computing with AI and machine learning is changing the way enterprises process data. Deploying AI models on edge devices can directly analyse and process data at the source of data generation, reduce dependence on the cloud, and improve the timeliness and efficiency of data processing.

• For example, in the Industrial Internet of Things (IIoT) scenario, edge devices can monitor the operating status of production equipment in real time through machine learning models, and respond immediately when abnormalities are detected to avoid downtime or accidents. The development of this "smart edge" is enabling enterprises to respond to complex business challenges more efficiently.

Trend 4: Data Privacy and Security

• Under the current increasingly stringent data privacy and compliance requirements, edge computing provides enterprises with a safer way to process data. By processing data locally, edge computing reduces the risk of data in transmission and reduces potential security vulnerabilities. In addition, processing sensitive data at the edge can avoid centralising all information in the cloud, reducing the risk of data leakage.

Trend 5: Hybrid Cloud and Multi-cloud Strategies

• The increasing popularity of hybrid cloud and multi-cloud strategies has promoted the flexibility and diversity of enterprise edge computing deployment. By combining edge computing with multiple cloud services, enterprises are able to build highly flexible computing architectures to optimise performance and costs. Hybrid cloud strategies allow enterprises to freely migrate workloads between local and cloud, while multi-cloud strategies provide enterprises with greater freedom to choose suppliers and business continuity guarantees.

  

The Technical Impact of Edge Computing on Enterprises

• Low Latency and High Bandwidth

Edge computing significantly reduces the latency of data transmission by moving data processing to the edge of the network. This is crucial for application scenarios that rely on immediate response, such as autonomous driving, industrial automation, and financial transactions. High bandwidth ensures that a large amount of data can be effectively transmitted and processed in a short time, avoiding network bottlenecks in the traditional cloud computing model. For enterprises, this means providing faster and more reliable services, thereby enhancing user experience and business competitiveness.

• Real-time Data Processing

Powered by edge computing, enterprises are able to perform real-time processing at the source of data generation without having to transfer all data back to a central data centre. This localised data processing method greatly improves the response speed of the system, allowing enterprises to make immediate decisions, especially in business scenarios that require rapid response, such as smart manufacturing and retail management. Real-time data processing also reduces the load on data transmission, allowing enterprises to manage and utilise their data resources more efficiently.

• Distributed Computing Architecture

Edge computing promotes the widespread application of distributed computing architecture, allowing enterprises to allocate and process tasks more flexibly. Under this architecture, computing power is distributed to multiple edge nodes instead of being concentrated in a single data centre. Distributed architecture not only improves the reliability and fault tolerance of the system, but also reduces the risk of single points of failure, allowing enterprises to maintain efficient operation of the system when facing large-scale data processing needs.

• Management and Maintenance of Edge Devices

To ensure the efficient operation of edge devices, enterprises need to adopt advanced management tools to support remote monitoring, configuration management and troubleshooting. In addition, the introduction of automated management technology will help enterprises simplify the maintenance process of edge devices, reduce operating costs, and improve the overall stability and security of the system.

Through low-latency, high-bandwidth connections, real-time data processing capabilities, the flexibility of distributed computing architecture, and effective management of edge devices, edge computing is having a profound impact on enterprise technology strategies and helping enterprises compete in fierce competition. maintain a leading position in the market.

The Business Impact of Edge Computing on Enterprises

• Cost-effectiveness

Edge computing can effectively reduce the operating costs of enterprises. By processing data locally, enterprises reduce their dependence on central data centres and remote cloud services, reducing the cost of data transmission and storage. In addition, the local processing of edge computing also reduces bandwidth requirements, thereby further saving costs. This efficient cost management enables enterprises to optimise resource utilisation and achieve higher cost-effectiveness while maintaining high performance.

• Enhanced Customer Experience

Edge computing provides enterprises with a powerful tool to improve customer experience. Its low latency and high bandwidth characteristics ensure that applications and services can respond to customer needs more quickly. At the same time, edge computing supports real-time data analysis, and enterprises can provide personalised services and recommendations based on user behaviour and preferences, thereby enhancing customer satisfaction and loyalty.

• New Business Model

Edge computing not only optimises existing businesses, but also opens up new business models for enterprises. Through distributed computing, enterprises can develop and provide new services such as real-time data analysis and intelligent device management, which is particularly prominent in smart cities, the Internet of Things and other fields. The widespread application of edge computing is creating new sources of income for enterprises and promoting the diversification of business.

For example, companies can help other companies optimise their data processing processes and open up new market opportunities by providing edge analytics services.

FS Enterprise Network Solution with Edge Computing Functions

In enterprise networks, the application of edge computing is particularly important. It greatly improves the performance and response speed of the network by moving computing and storage capabilities closer to the location where data is generated. The FS solution shown in the figure is a typical application case.

Network Architecture and Edge computing functions

• 1. Access Layer (Access):

• Function: This layer is responsible for the connection and data transmission of terminal devices (such as PCs, wireless access points AP-N515, etc.). The access layer is connected to the aggregation layer through S3410-24TS-P and S3910-24TS switches, and uses 10G optical fibre links to ensure that terminal devices can quickly access network resources.

• Edge Computing: Deploying edge computing devices at the access layer can pre-process data locally and reduce the burden and delay of the network core.

• 2. Aggregation Layer (Aggregation):

• Function: The aggregation layer is connected through high-bandwidth 40G optical fibres to concentrate and transmit the data of the access layer to the core layer. The S5860-20SQ switch is responsible for data aggregation and transit.

• Edge Computing: The aggregation layer is the key location for edge computing. Deploying edge computing nodes here can realise complex data analysis and processing, thereby reducing dependence on remote cloud services and realising real-time data processing.

• 3. Core Layer (Core):

• Function: The core layer undertakes the backbone task of data processing and transmission of the entire network through the S5860-48SC switch and 100G optical fibre link, which is the key guarantee of network performance.

• Edge Computing: The core layer equipment has powerful computing and storage capabilities, supports large-scale data processing, and also provides necessary backup support for edge computing nodes to ensure the efficient operation of the campus network.

Covered Product Introduction

• 1. S5860-48SC, S5860-20SQ Switch: These core and aggregation layer switches support high-speed data transmission (40G/100G), have high throughput and low latency, and are suitable for deploying edge computing nodes. They can quickly process and forward large amounts of data flows from the access layer and aggregation layer, providing sufficient bandwidth support for edge computing.

• 2. S3410-24TS-P, S3910-24TS Switches: At the access layer, the S3410 and S3910 series switches provide Gigabit Ethernet connections for terminal devices and support primary data processing for edge computing. The PoE function of these switches also facilitates the deployment of wireless access points, further improving the flexibility and ease of use of the network.

• 3. QSFP-SR4-40G, QSFP-SR4-100G Optical Modules: These optical modules support high-speed fibre connections, ensuring efficient data transmission between the core and aggregation layers, reducing network latency and improving the overall performance of edge computing.

• 4. AmpCon™ Management Platform: The platform provides centralised management and monitoring of the entire network, supports unified scheduling and optimised configuration of edge computing nodes, and ensures the reliability and security of the campus network.

  

Through this network architecture, enterprises can deploy edge computing nodes at the core and aggregation layers, optimise network performance, improve data processing efficiency, and reduce latency. FS medium and large campus network solutions can not only meet current business needs, but also provide flexible support for future expansion and upgrades, which is a strong guarantee for the digital transformation of enterprises.

Summary

Edge computing is rapidly becoming a key technology for enterprises to enhance their competitiveness. Through the integration of 5G, IoT, and AI, edge computing provides low-latency, high-bandwidth real-time data processing capabilities. It not only optimises the technical architecture of enterprises, but also brings cost-effectiveness and new business models, providing unlimited possibilities for future development.

Ready to innovate? Let's transform your business with edge computing solutions! If you need professional network deployment solutions, FS is always here to support you and help you seize the opportunity in the era of edge computing. Please feel free to consult us!