Types and applications of edge computing

Edge computing is the next step in supercloud computing. As the demand for data grows, more organizations are looking to bring the cloud closer or allocate computing resources across a wider network. This shift to the margins has many benefits, but it can also be a complicated one.

Type of edge computing
The first step to getting the most out of edges is to understand the different types of edge computing. Edge networks come in a variety of shapes and sizes, each with unique advantages and disadvantages. Global spending on edge computing is expected to reach $176bn this year. So it's important to know what fits your needs and goals.

Divide edge types by technology
There are many ways to classify edge technologies and networks. Therefore, there is no conclusive answer as to how many types of edge computing exist or what those categories are.

One of the easiest ways to demarcate boundaries is in terms of the system and platform on which the computation takes place. Here are some of the most common categories according to this definition.

Edge of cloud
Cloud edge is the first computing type under this classification system. As the name suggests, these networks are more similar to traditional cloud computing. It uses large data centers, but unlike traditional approaches, these centers are relatively close to the end user and typically serve applications built for a specific purpose.

These systems provide impressive latency improvements while maintaining the capacity of traditional clouds. While 58% of cloud users can achieve latency of less than 10 ms in some scenarios at a nearby edge data center, only 29% of cloud users can do so at a traditional cloud data center.

However, these deployments can be more expensive and not accessible to all because they depend on the data centers available in the user's area. As such, they are best suited for large enterprises or operations with high data requirements near existing infrastructure.

Equipment edge
Device edge is probably what most people also think of when they think of edge computing. A growing number of organizations have noticed remote transmission delays between hosting locations and are beginning to adopt these networks to bring the computing process closer to the data source.

Device edge networks distribute computing tasks across local devices, such as phones, smart gadgets, and routers. This provides minimal latency while sacrificing the capacity of the limited processing power of these devices. As a result, these networks often serve specific use cases rather than being a general alternative to cloud computing.

Successful implementation of device edge networking requires an understanding of the user's goals and the functionality of the accessible device. These systems are best suited for simple, highly specialized applications, such as predictive maintenance, that depend on the machine at hand.

Calculation of the edge
The computing edge environment provides a middle ground between the device and the cloud edge network. These can distribute computing tasks on small, dedicated machines such as the edge of the device, or they can utilize miniature data centers (MDCS).

MDCS can come in a variety of sizes, typically between 50 and 400 KWH, and can have only one rack or host several racks. They are also typically modular, making them more scalable and adaptable than traditional data centers. These techniques allow computational edge systems to take up less space and be more flexible than cloud edges, but have higher power than device edges.

Computing edge networks are ideal for companies that have a variety of edge computing needs but may not have access to larger data centers nearby. While the cost of installing MDC will be higher than that of a device edge environment, it will support a wider range of use cases.

Edge of sensor
The sensor edge is located at the other end of the cloud edge. These systems perform computational tasks as close as possible to the source of the data, utilizing Internet of Things (IoT) devices to perform basic computations at the sensor level.

There are more than 12 billion active iot endpoints in the world today. Each device represents a data collection point, and sensor edge computing moves some of the analysis process to these endpoints to maximize iot performance. However, since these endpoints typically have minimal hardware, these computations are far less complex than those seen in cloud edge networks.

Sensor edge computing offers some of the lowest latency possible, but the lowest computational power. Therefore, these environments are best suited for simple, device-specific tasks, such as using motion detection to trigger connections to other higher capacity systems.

Edge types by location
You can also divide different types of edge calculations based on the physical location of the deployment. These can fall into any of the technology-based categories, or a mix, distinguished by how computing tasks are distributed across different domains.

Branch edge
Branch edge environments are characterized by a dedicated edge network for each branch in the organization. Also known as LAN edge systems, these networks are designed to provide low-latency support for the specific needs and goals of each office. Therefore, this is ideal for organizations with multiple branches and specific location operations.

While 99.9 percent of companies are small, it's still common for businesses today to have multiple branching edges. Adopting a branch edge approach may be ideal for these organizations, although those departments with less specialization may require other approaches. An enterprise with one location and a centralized edge environment can technically be classified as a branch edge, requiring only one branch.

The enterprise edge
The enterprise edge distributes computing tasks across multiple branches and locations. These systems typically use a combination of device and computing edge Settings to take full advantage of all available resources within the enterprise.

Each location hosts the edge computing infrastructure in the enterprise setting, but does not necessarily perform all internal functions. The idea behind these environments is to support greater flexibility in adjusting the way computing resources are allocated to changing needs. Therefore, this is more suitable for large organizations with many different needs but less location-specific specialization.

Mobile edge
The most flexible and dynamic of these edge environments is the moving edge. These Settings distribute computing across mobile devices, including non-stationary iot devices and smartphones.

About 85 percent of American adults own a smartphone, and more than half own a tablet. Such a large array of mobile devices provides considerable distribution and computing power for mobile edges. However, these environments are still not as powerful as environments that use data centers.

For businesses where most work is done on mobile devices, mobile edges are ideal. Operations that involve more travel than staying in the same office building can benefit the most from these environments.

When to use various types of edge computing
To determine which type of edge computing to use, you first need to know what each offers. Cloud and computing edge deployments tend to offer greater capacity, while device and sensor edge deployments offer lower latency and cost. Thus, the first two are better suited for resource-intensive processes or processes with many different requirements, while the latter are better suited for highly specialized tasks.

In addition, location requirements should be considered. A more centralized enterprise should use either branch edge or enterprise edge, or the latter if there is higher computing demand. In contrast, businesses with more flexible workflows and locations may prefer to move edges.

Security is another issue, with 85% of edge adopters identifying it as their main challenge in these environments. With fewer distributions, cloud and computational edges are generally easier to secure and are therefore well suited for more sensitive applications. Branch edges may be better if different locations have different security requirements, but enterprise edges are sufficient when these requirements are consistent across branches.

Choose the right edge method for your application
Edge computing comes in many forms, probably more than many people realize. Understanding these different types and their unique advantages and disadvantages is the first step to taking advantage of the technology. This is the best choice when you know what to look for and how to benefit from it.

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Types and applications of edge computing