Comparison of Edge Computing Implementations

We have already discussed the benefits and importance of Edge computing for processing large-scale data and why it is preferred over cloud computing. For all data processing requirements, cloud computing has been the most preferred solution for the past 10 years. But with the growth of intelligent devices, the Internet of things, V2X communications and Augmented reality, this trend is shifting towards Edge computing.  The main reason behind such rapid adoption of Edge computing technology is the delays and latency issues associated with cloud computing that needs data to be sent to cloud for processing and brought back to the application for the response. To tackle the shortcomings, we need to process data nearest to the devices. There are several types of Edge computing implementations. Let’s discuss the comparison of Edge computing implementations in detail.

Comparison of Edge computing implementations

The three most famous and most adopted implementations of Edge computing are:

• Fog Computing
• Cloudlet
• Mobile edge computing

Fog computing:

Fog computing is one of the types of implementation that use Edge computing concept. In this implementation, we create a distributed network that connects two environments. The first environment is the application and the technology that generate the data to be processed and the second environment is a data center where this data is to be processed.  In this case, the data centers are at the nearest location to the application. It is a solution to the cloud’s limitations, which reduces amounts of data and its movement across the network and performs processing at the edge of the network.

Benefits of Fog computing:

Fog computing gives choice to the organizations to process the data wherever it is most appropriate for the benefit of the organization. It creates low latency connections. Users can enhance the security in many ways like introducing virtual firewalls. In short, it reduces congestion, eliminates bottlenecks and enhances security.

Where to implement this solution:

• Applications that need very low latency. For example health monitoring and other emergency response Apps.
• Geographically distributed Sensor networks. like smart cities and environment monitoring etc.
• Fast mobile Apps like a smart connected vehicle or a rail.
• Large-scale distributed networks e.g. smart grid.

Cloudlet:

A cloudlet is basically a microdata center used for processing the data, This Cloudlet is located at the edge of the network.  It can be defined as a “small data center in a box” or a cloud warehouse that is at the nearest location to the application. You can think about it as an implementation used to bring the cloud closer. They are used to provide services to mobile devices, smartphones, Tablets, and wearable devices.

Benefits of Cloudlet:

This improves the overall performance and latency that is associated with remote cloud data-centers. These small data centers are very efficient and provide fast responses.  It possesses sufficient compute power (i.e. CPU, RAM, etc.) to offload resource-intensive computations from one or more mobile devices. It has excellent connectivity to the cloud and tackles the issues related to batteries with a finite amount of energy.  In short, it is a cloud that is sitting closer to the application and improves many issues that happen when we use remote cloud warehouses.

Where to implement this solution:

• When we need to provide services to Mobile devices, Smartphones, tablets, and wearable devices.
• Applications that are resource intensive and interactive, like Augmented reality.
• Wearable cognitive assistance systems like Google Glass.

Mobile Edge computing:

Also, in this implementation of edge computing the basic idea is same, i.e. do the computing nearest to the device. In this case, the computing is done at the edge of the mobile network. At present, most of the mobile applications handle data at the remote servers located far from the end devices. In Mobile Edge computing the processing is brought closer by integrating it to cellular base stations.

Benefits of mobile edge computing:

• Reduce congestion in mobile networks.
• With the growth of smart connected devices, 5G Mobile Edge computing can handle the traffic in a better and efficient way.
• It reduces latency in a far better way.
• When we bring data closer to the end user, they can have a better experience, and it matters a lot for new applications and trends.

Where to implement this solution:

• Augmented reality solutions.
• Video streaming services.
• Automated car applications and autonomous solutions.
• Internet of Things applications.

These were some of the most common implementations of Edge computing. This comparison shows that different implementations are suitable for different situations. Each one has its own benefit and in-depth procedure of implementation.  However, it is important to know how a particular solution is beneficial for a scenario.

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