What is Edge Computing?

Although the cloud has proved its usefulness for business, offering reduced downtimes and the lowering of costs, it does have some drawbacks including a requirement for internet connectivity, reduced speed, and security concerns.  
To address such issues, edge computing – where data is processed as close as possible to the actual physical location that creates the data - has been developed. This saves bandwidth and reduces latency to deliver the high-speed digital experiences today's users expect.  
With edge, data is processed in the central data center - only the most important data is transmitted. For example, a security camera in a remote warehouse uses AI to identify suspicious activity and only sends that specific data to the main data center for processing. So, instead of the camera clogging the network 24 hours a day, every day, transmitting all of its footage, it only sends relevant video clips. This frees up the business's network bandwidth and computer resources for alternative uses. 
With edge computing, decisions can be made at the collection point or at a location physically close to the collection point. This noticeably improves the time taken to make a decision based on the data, which is vital for situations that need real-time decisions, such as directing autonomous cars when communicating with each other. 
At its simplest, edge computing is the practice of capturing, processing, and analyzing data near where it is created. It is data analysis that takes place on a device in real-time, processing data locally whereas cloud computing refers to processing data in a data center or public cloud, often far from where the data is created. 
It’s “everything not in the cloud”, says Ryan Martin, principal analyst with ABI Research, “If we think about a hub-and-spoke model, the cloud is the hub and everything on the outside of the spokes is the edge.” This decentralized way of computing lets organizations move processes such as analytics and decision making closer to where the actual data is produced. 
Edge computing is most pertinent when speed and/or efficiency are the vital elements. When computing is physically closer to the source of data, it can be analyzed in near-real time.  
Edge computing can also cut down the volume of network traffic. Large volumes of data can be processed close to the source using small, distributed data centers, reducing the amount of Internet bandwidth taken up. That, in turn, cuts costs and ensures that applications can be used more effectively in remote locations.

How can Edge Computing be Used to Improve Sustainability?

Edge computing uses less power and reduces latency compared to central servers located in cloud data centers. It cuts the volume of data transmitted to and from the cloud and reduces the impact of this traffic on the network. As a result, it also reduces operational costs for cloud service providers (CSPs). 
By cutting back data center usage, energy consumption is also reduced, which in turn improves environmental impact. As well as cutting electric power consumption and greenhouse gas emissions, edge computing can also save money by reducing data center cooling costs. 


Edge Computing vs Cloud Computing 

Edge computing improves the security and privacy of your data. With edge computing, you can store your data on the edge of a network, rather than in one central location. This means it is a lot more difficult for hackers to gain access to sensitive information or steal it from your device, something that is easier if everything is only stored in the cloud. That's because, with edge computing, hackers would need access to numerous points of entry before they could break into any usefully large datasets.  
Effectively, the difference is that those functions that are most efficiently optimized by the computing split between the end device and local network resources will be done at the edge, while big data applications that gain most by bringing together data from everywhere and running it through analytics and machine learning algorithms running in hyperscale data centers will remain in the cloud. 

While edge computing and related applications are complex issues, here at Techbuyer we have the expertise needed to help you navigate those issues to best optimise your organization’s compute requirements.