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Defining edge computing architecture can be challenging. Because edge computing is an increasingly popular style of architecture that supports multiple use cases, articulating a single, comprehensive definition can be difficult. In fact, you¡¯ll likely receive a different definition depending on who you ask.

Elements of edge computing are wide-ranging and can include mobile devices, IoT, smart environments, the cloud, and on-premise infrastructures. Edge computing can also apply to driverless cars, robotics, manufacturing, and more. 

This article will outline a ¡°big-picture¡± snapshot of edge computing, discuss its fundamental properties, and then examine a few potential uses. 

All About Edge Computing

Edge computing brings data and computational power closer to the sources of the produced data to provide savings on bandwidth and response times. It has no single topology but refers to the architecture as a whole. 

Because edge computing relies on the cloud to store and process data close to the applications and users that consume it, a high-speed internet connection is necessary for reliability. With data situated near its consumed location, faster applications with greater availability are possible. 

Edge Computing Advantages

By keeping data near the edge of the network, edge computing provides advantages that include:

• Enhanced bandwidth and availability
• Improved response times 
• Faster data analysis in addition to the higher availability we¡¯ve discussed. 
• Reduced latency 
• Safer data processing through distributed processing and storage.  

With IoT devices and edge servers, companies can scale efficiently and cost-effectively without investing in private data centers that require maintenance. 

To accomplish this kind of scaling, edge devices collect and store data before sending it to specific servers, utilizing data visualization and analytics, caching and buffering, data filtering, and real-time data processing. Consequently, expansion can be as easy as partnering with a local edge data center and testing new markets. New infrastructure is not required¡ªonly edge devices for setup. If the market is not optimal, uninstallation is simple.

Interconnectivity With Edge Computing Architecture

Edge computing moves processing power closer to the client with edge data centers and embedded data storage directly on devices. As a result, applications are shielded from data center outages.

Edge computing can be viewed as a layered approach, with the top layer comprised of data centers, including central and interconnected regional data centers. The edge layer is one level deeper and is composed of smart cars, oil platforms, retail shops, medical clinics, and the list goes on. Edge devices comprise this layer and include IoT devices, smartphones, sensors, and other internet-connected devices. The edge layer runs on a local network powered by wireless, 5G, fiber, or older legacy hardware.

Inside the edge layers, there are individual devices, smartphones, laptops, and other IoT devices that are all capable of communicating with the edge data center.

A key feature in this architecture is that databases are embedded within edge devices and allow continuous processing if a large-scale cloud database server fails. Individual devices synchronize captured data across the environment¡ªbetween cloud and edge databases and between embedded databases on devices¡ªensuring it is always available.

As major cloud service providers increasingly offer edge computing services where data centers can be established in specific cities, on-premises, or in 5G networks, edge computing initiatives have discovered increased flexibility and simpler implementation.