In this article, we will focus on different edge computing examples based on computing resources’ physical location. They include:

In a typical closed control loop system, sensors act as the initial trigger point for sending events to the backend systems. For example, in a video camera, an optimal model is to send live streams only when there is motion. Capabilities such as motion detection and tripwire detection can eliminate the need to send continuous traffic to the cloud for processing until a motion is detected. These functionalities require edge computing right at the sensor. In most cases, the edge computing capacity is minimal and is used for a very targeted feature integrated into the product.

Customers deploy different types of devices to perform specific functions—for example, shop floor motors, X-ray machines, and vending machines. Data from this equipment can be collected and analyzed to ensure safe and seamless operations and predict maintenance needs in advance. Computing resources are deployed closer to the devices to process these workloads and deliver low latency responses. Small form factor appliances and gateways are commonly used to provide both compute and physical connections to legacy interfaces.

The primary function of a router is to forward packets between networks. They act as the demarcation point between the external systems and internal networks. Some enterprise routers provide built-in compute or the ability to plug additional compute modules and be used to host applications. In this model, a single router can perform both packet routing functions and provide infrastructure to host edge applications.

A branch is a location other than the main office designated to perform a set of functions. Each branch uses various applications to perform its daily functions. In the case of a retail clinic, it might be a Point of Sale system, or in the case of a health clinic, it may be an Electronic Medical Record. Such business-critical applications are hosted on edge compute at the branch to provide low-latency access to users and provide business continuity. The edge computing appliances typically have more capacity than the previous types of edge compute servers and can host multiple virtual network functions and applications on the same hardware. Sometimes, “branch edge” and “Local Area Network edge” are used interchangeably.

In a distributed enterprise environment with many branch locations, computing resources can be shared among the branches to drive economies of scale and simplify management. In this model, instead of deploying edge computing instances in each location, the edge computing resources can be implemented in a shared site connected to the enterprise network. In this model, the capacity and capabilities tend to be much higher and can be used for applications that require more processing power and resources.

As customers migrate to the cloud from their existing data centers, smaller variants of data centers have emerged to address rapid deployment and portability for special events, and disaster management. These can be deployed closer to the customer. The form factors typically vary from suitcase size to shipping container size.

Cloud service providers have used services built for a specific purpose closer to the users to optimize specific functions such as content delivery. Some refer loosely to Content Delivery Networks (CDN) and caching services as a cloud edge; however, they were not built to host general-purpose workloads. While the initial attempts were focused on caching and content delivery, newer services such as local zones redefine cloud edge. In addition, cloud service providers have created many edge solutions that fit into some of the previous models discussed.

The wireless service providers provide nationwide service using a very distributed network. The service locations tend to be closer to the customer than the cloud datacenters. When these locations are multi-purposed to provide wireless services and host edge computing services, it becomes a unique model for edge computing and has distinct advantages. In the mobile edge computing model, computing resources are deployed in service access point (SAP) locations or other locations in the core. Applications running on these edge computing servers can be accessed from mobile endpoints through 4G or 5G connections.

To further understand the benefits of mobile edge computing, we will use latency as a benchmark and review how it influences the 5 C’s of latency (connection, closeness, capacity, contention, and consistency). Concerning connection and closeness, not only is this edge closer than the cloud regions, but it also inherits the benefits from the transport characteristics of 5G and the savings from the direct path from the wireless devices bypassing the internet to the computing resources. Capacity is another crucial differentiator against many of the other edge computing models. With the ability to host various compute instances such as Graphical Processing Units, the mobile edge provides a scalable edge infrastructure. By processing and filtering many requests right at the mobile edge, the mobile edge can reduce the contention at the backend servers. Bypassing the internet and providing a shorter direct path also influences the consistency of the experience. 

While some of the other edge models can be closer than the mobile edge, when you consider the overall benefits, the mobile edge strikes the right balance. In many of the other models, the hardware is located in the customer site, and hence additional effort is needed to handle power, space, cooling, management, and physical safety. Mobile edge computing allows users to consume applications as services, making it easier for customers to access low latency applications without deploying hardware in their networks.

In summary, each of the edge computing models has a sweet spot segment and associated challenges. Our recommendation is to start with the customer’s application needs and evaluate the best edge computing model.

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