What is Edge Computing? Benefits and Use Cases: The Ultimate Guide

There has been a significant increase in the amount of data generated and processed by devices connected to the internet. With this increase in data, the traditional centralized approach to computing and storage in the cloud is proving to be inefficient and costly.

Edge computing provides a distributed computing model that brings computation and data storage closer to the source of data generation. In this guide, we will explore what edge computing is, how it works, its benefits, and real-world use cases that highlight its potential.

What is Edge Computing?

Edge computing provides distributed computing paradigm that brings computation and data storage closer to the location where it is needed, such as the source of data generation and consumption. You can achieve it by placing computing resources, such as servers, routers, and other network drivers, at the network’s edge, rather than relying solely on centralized computing resources.

Edge computing involves analyzing data closer to the source of its creation, rather than transmitting it over long distances to centralized servers.

• It reduces latency
• Improves response times
• Lower bandwidth requirements
• Enhances overall system performance.

By leveraging the edge computing approach, organizations can improve their ability to, making it an increasingly important approach for various use cases.

How Does Edge Computing Work?

Edge computing captures and processes all the information and data as close to the source as possible. You have to place computing resources such as servers, routers, and other network devices at the edge of the network, such as within a smart device, factory floor, or retail store.

When data is generated or consumed, it is processed and analyzed at the edge, rather than being transmitted over a long distance to centralized data centers for processing. The data is migrated to the edge model with the help of IoT devices. The approach reduces time and latency with lower bandwidth requirements.

Edge computing typically involves a three-tier architecture comprising the edge, fog, and cloud layers.

1. The edge layer consists of devices, sensors, and gateways that generated data.
2.  The fog layer consists of nearby computing devices that process data before sending it to the cloud.
3. Finally, the cloud layer is the centralized data center that provides advanced computing resources and analytics capabilities.

Edge computing can be deployed on-premises, in a public cloud, or in a hybrid cloud environment, depending on the specific needs and requirements of the organizations. The deployment model selected will impact the location of the edge resources, how they are managed and secured, and how they interact with other computing resources in the system.

Edge Computing Vs Cloud Computing

Edge computing and cloud computing are two distinct computing models that have their own advantages and use cases. While both models involve processing and storing data, there are key differences between the two.

Cloud computing is a centralized computing model that involves storing and processing data in a centralized data center, typically operated by a third-party cloud service provider. The data is accessed over the internet using a variety of devices such as smartphones, laptops, and tablets. Here is a detailed comparison of the two;

Why is Edge Computing Beneficial for You?

Edge computing has become one of the most popular architectures for achieving efficiency. As it supports distributed computing to deploy and store of the data closer to the sources, many businesses are shifting their focus to edge computing over other.

But decentralization in computing can be overwhelming, demanding high levels of control and monitoring while moving from a legacy centralized computing model. Edge computing effectively solves network issues while dealing with large amounts of data. These factors are creating more demands for edge computing serving different benefits as follows;

1. Reduced Latency

Edge computing reduces the time it takes for data to travel from the source to the cloud data center, resulting in faster response times and reduced latency. Quicker response times are crucial for real-time applications, such as IoT, where even milliseconds matter.

2. Improved Performance

By processing data closer to the source of generation, edge computing can improve application performance, resulting in better user experience and increased productivity. They are crucial for applications that require high performance, such as autonomous vehicles, video streaming, and virtual reality.

3. Lower Bandwidth Requirements

Edge computing can reduce the amount of data that needs to be transmitted over the network, reducing network congestion and bandwidth requirements. Lower bandwidth can result in reduced costs and improved network performance.

4. Enhanced Security

You can easily enhance your network security by processing and storing sensitive data locally, reducing the risk of data breaches and cyber-attacks. Industries dealing with sensitive data, such as healthcare and finance can benefit from edge computing.

Related Read: Healthcare Data Security Checklist

5. Increased Reliability

By distributing computing resources across the network, edge computing can increase system reliability and availability. It occurs because of one edge node fails, other nodes can take over, ensuring that the system remains operational.

6. Cost Savings

Edge computing can result in cost savings by reducing the amount of data that needs to be transmitted to the cloud data center, lowering network and storage costs. By processing data locally, businesses can reduce cloud data center costs, such as bandwidth costs and storage costs.

Some of the Use Cases of Edge Computing

After understanding every aspect of edge computing, let’s dive into some of the use cases below.

🔹 Retail

Every retail business aims for a seamless, flexible, and customer-centric experience. Edge computing will empower the retail capability enabling the human-centered experience at the heart of this model.

Edge computing enables real-time processing and analysis for applications like inventory management, personalized advertising, and customer analytics. Retailers can improve their operations and customer experience by processing data at the edge.

🔹 Healthcare

Edge computing is used in healthcare applications to enable real-time data processing and analysis for medical devices like wearables, implants, and monitoring systems. By processing data at the edge, healthcare providers can improve patient outcomes and reduce healthcare costs. As healthcare deals with a large amount of sensitive data, which can be processed and analyzed securely at the edge.

Edge computing in healthcare has played an important role in creating an impactful and seamless experience for customers. Healthcare providers are implementing edge computing in different functions associated with healthcare such as robust-assisted surgery making it easier for surgeons and procedures less complicated and easier for patients.

Related Read: 3 Important Factors in Healthcare Cloud Migration Strategy

🔹 Video Streaming

Edge computing is used in video streaming applications development to reduce buffering and improve video quality. By caching video content at the edge, video streaming services can reduce the amount of data that needs to be transmitted over the network, resulting in faster and more reliable video streaming.

Enabling good user experience has been possible by leveraging edge computing for both existing and emerging features. Users are made accessible to features such as content suggestions, personalization, and interactive capabilities. Providers are able to deliver live content for events, original or on-demand content on the large scale.

🔹 Manufacturing and Industrial Processing

Edge is widely used in IoT applications, where it provides real-time data processing and analysis for devices like sensors, cameras, and other IoT endpoints. Businesses can reduce latency and improve the efficiency of their IoT applications.

IoT has revolutionized the functioning and operations of manufacturing and industrial processes such as agriculture. The service providers can monitor their equipment performance and finished products. Edge computing applies processing that delivers the speed required for manufacturing processes. The applications of automation make real-time monitoring of inventory and maintenance efforts.