Edge computing is a networking architecture related to computer networking, cloud computing, and the Internet of Things (IoT) designed to improve performance and resource allocation when compared with traditional, on-premise, or cloud computing. In this networking article, we seek to answer the question: what is edge computing and discuss some examples of how it works.
What is Edge Computing
Edge Computing is a type of network computing architecture that is defined by the geographic location or distribution of computing resources. The goal is to locate the network near – or at – the location of your data. It is not meant to replace the cloud (whereby networking resources are located around the globe), but rather, it seeks to add the cloud to the same location as the data source. The main goal is to reduce response time, especially in crucial cases that need immediate or emergency response, like self-driving cars and fire alarm systems.
The idea behind edge computing has been around for some time, even though the technology itself is pretty new. Edge computing emerged as a response to the increase of various IoT and smart devices, which are the result of cloud, artificial intelligence, and data science converging.
Benefits of Edge Computing
With all of the above in mind, below are some of the benefits of edge computing for developers and development teams:
- Reducing costs by using less bandwidth.
- Increasing performance by reducing response times.
- Enabling IoT – without edge computing, self-driving cars are improbable.
- Enabling real-time apps such as facial recognition.
- Enhancing artificial intelligence (AI) function via AI chipsets.
- Integrating with cloud computing in the shape of the distribution of roles.
- Empower virtualization technology to deploy more related applications.
- Creating the ability to store huge amounts of data (Big Data) that is hard to upload via the Internet.
- Solving data sovereignty and data sensitivity in some industries, like banking and healthcare.
- Better security compliance for cases that require critical requirements.
- Avoid unpredictable network disruptions.
How Does Edge Computing Work?
Edge computing is focused mainly on the server’s location. Traditional, on-premise computing stores data locally on the user’s computer. From there, data goes out via the corporate LAN or the internet WAN, then returns back to the user. This old method still makes sense for many types of applications that need real-time results.
However, the main challenge in that old approach is the number of online devices and the amount of data generated; it increases in such a way that it can overwhelm the storage capacity of typical on-premise infrastructures, as well as cause network congestion that can affect performance negatively. The main difference between on-premise and edge computing is that it changes the focus from a central data center into the logical edge concept, where computing resources are located near where the data is generated.
To further clarify the difference between edge computing and other computing models, consider the following:
- Early computing: Centralized applications and data are run and stored via terminals on one isolated, huge, centralized computer.
- Personal computing: Decentralized applications and data are run and stored locally on every person’s computer.
- Cloud computing: Centralized applications and data run and are stored remotely overseas in a cloud providers’ data centers.
- Edge computing: Centralized applications and data run and are stored close to users’ high-capacity data centers on the network edge.
Edge Computing Examples
Thanks to its various benefits and diversity, edge computing – when paired with cloud computing or as a standalone resource – has made a big difference for many life industries, including:
Manufacturing: Edge computing in the industrial manufacturing sector can enhance monitoring, empower real-time analytics, and enable machine learning. This can reduce production mistakes via artificial intelligence and employs smart sensors to provide real-time insights for making better business decisions.
Farming: By receiving data from sensors, the modern farming business can produce crops indoors, even if sunlight and soil aren’t always available. This method can increase the speed of growing crops to double traditional time. These sensors need an edge cloud in order to collect data about irrigation status and nutrient density for improving growth and harvesting algorithms.
Network optimization: For Internet providers, edge computing provides performance analytics. It helps each user’s device to select the best reliable and low-latency paths for better Internet performance. In other words, edge computing guides the traffic across the Internet to improve the user experience and serve peek hours.
Workplace safety: in remote or dangerous workplace environments, when monitoring is important and difficult at the same time, edge computing can offer great help. By real-time analysis of data that comes from safety sensors and on-site cameras, the company can ensure employees’ safety and safety protocols compliance.
Improved healthcare: The healthcare sector is a prime beneficiary of edge computing features. From real-time data and analytics needs, to highly sensitive patient data and the continuous stream of medical data and records generated that need machine learning for smart automation.
Transportation: For transportation businesses such as Uber, it’s crucial to perform real-time analysis based on daily terabytes of data gathered concerning location, speed, vehicle condition, road, and traffic conditions.
Retail: As is the case in the manufacturing and transportation industries, retail also relies on a huge amount of data generated on a daily basis. From cameras to warehousing and the tracking of discount campaigns. Nevermind the dynamic nature of retail businesses.