What is edge computing from a hardware perspective?

Edge computing has exploded due to the massive amounts of data generated by IoT and IIoT devices. As 5G networks develop and 5G becomes more common, new devices coming online will generate more data than ever before. As a result, many businesses are finding it very effective to use edge computing to perform real-time, low-latency data analysis. Edge computing makes it possible to process data locally close to the source of data generation.

What is edge computing?

Edge computing is a decentralized computing framework that places computing power closer to the source of data generation. Edge computers are like mini data centers that process and store data, sending only necessary data to the cloud for storage or post-processing. For example, edge computing solutions are deployed near IoT and IIoT devices, providing real-time data collection, storage, and processing. This reduces the amount of latency involved and reduces the amount of internet bandwidth required for IoT devices.

The rapid development of edge computing is due to the fact that all data generated by IoT devices and industrial IoT devices are sent to centralized data centers for processing and storage, which makes edge computing easily solve latency and bandwidth problems.

Edge computing reduces the burden on data centers by processing and storing IoT and IIoT device data locally at the source where the data is created. Sending less data to the data center can save a lot of bandwidth costs for organizations that deploy edge computers. In addition, processing data locally significantly reduces latency because the data does not need to travel a long distance from the source device to the data center and back again. As 5G becomes more common, edge computing will only become more common and faster, relying on edge computing to improve the experience of organizations.

Edge computing is critical to organizations and businesses because of the insights generated by collecting, processing, and analyzing data generated by the thousands of sensors and connected devices common in industrial environments, such as manufacturing facilities.

Analyzing the data generated by IoT and IIoT devices can provide insights into a business’ operations, enabling organizations to quickly act on real-time data. The ability to react to insights in real time enables businesses and organizations to improve their productivity and the quality of the products or services they provide. That said, to extract valuable insights from data, computing power must move to the edge, close to the source of data generation.

Despite the growing popularity of edge computing, cloud computing still has its place in today’s modern world. Edge computing complements cloud computing by supporting applications that require real-time, low-latency data processing.

In edge computing, the edge refers to the source of data generation. For example, if you have deployed IoT devices or sensors to monitor the growth of crops, the edge will be close to the sensors and IoT devices that generate the data. The edge is different from the cloud, which is often located thousands of miles away from the devices that generate the data. That is, the question of where the edge is is different from one application to another because it depends on the topology. However, in general, the edge is usually closer to the data generating devices than the cloud.

What are the benefits of edge computing?

Edge computing provides several benefits, as described below:

1. Low-latency computing

One of the main benefits provided by edge computing is that it offers much lower latency than cloud computing. Low latency is critical for applications that require real-time data processing and analysis, where every millisecond counts. While some applications may require 100 milliseconds of latency, there are mission-critical applications that require significantly reduced latency, which can only be achieved with edge computing. Edge computing offers lower latency because edge computers are typically deployed close to the source of data generation, shortening the distance the data needs to travel to be processed and analyzed.

2. Reduce bandwidth utilization

The second benefit of edge computing is that it reduces the amount of internet bandwidth required. Edge computing requires less bandwidth because data is collected, stored, and processed locally on edge computers, eliminating the need to transfer all raw data to a data center for processing and analysis.

That is, processing data locally does not mean that data does not have to be sent to the cloud, but that less data must be sent to the cloud. This is so because data that triggers a specific trigger is sent to the cloud for post-processing and analysis. Doing so reduces the required Internet bandwidth. For businesses and organizations with metered data plans, this will result in significant cost savings.

3. Reduce the burden on data centers

As the amount of data grows exponentially, people are looking for alternatives to relieve the pressure on data centers. Edge computing can relieve the pressure on data centers by storing and processing data locally on edge computing devices. Edge computers have come a long way and can be equipped with powerful processors and large amounts of high-speed data storage, allowing them to process and store data at the edge instead of in the cloud.

4. Workload Consolidation

Deploying edge computing devices can save businesses and organizations a lot of money by consolidating workloads onto fewer devices. This enables organizations to reduce their hardware footprint and reduce points of failure because fewer components can fail. In addition, by consolidating workloads using edge computers, businesses and organizations will have fewer devices to maintain and monitor.

5. Predictive maintenance

One of the benefits of deploying edge computers is that they support predictive maintenance. That is, edge computers can monitor data collected from various devices and sensors to ensure that machinery and equipment are operating properly and optimally. In addition, edge computers can use artificial intelligence and machine learning (ML) algorithms to detect when a failure may occur, prompting management to perform maintenance or replace components before a failure occurs. This can save companies a lot of time and money because maintenance can be conveniently performed without suddenly stopping production.

6. Data Security

Edge computing provides data security because less data needs to be transferred to the data center, thereby reducing the chances of data being mishandled or misappropriated while in transit to the data center. In addition, edge computers are equipped with TPM 2.0, which protects the device through authentication and key management. In addition, distributing processing, storage, and applications across various computing devices makes it difficult for a single outage to shut down the entire network.

7. Reliability

Edge computing hardware is ruggedized, making edge computers more reliable than ever before. Rugged edge computers can be deployed in remote and challenging environments, while they can withstand harsh environmental factors that servers and regular desktop computers cannot withstand. In addition, edge computers are equipped with a variety of wired and wireless connectivity options, ensuring that edge devices can remain connected to the Internet even in remote environments with unstable Internet connections.

Disadvantages of edge computing

Here are some of the disadvantages associated with edge computing:

1. Scalability

Scaling cloud computing is easier than scaling edge computing because more storage and computing power can be easily added with the click of a mouse button on the cloud. This is different from scaling edge computing, where an organization must add or physically upgrade equipment to get more computing power or storage space.

2. Security

Securing a distributed edge computing network can be difficult and often requires physical access to each individually deployed device. Additionally, adding multiple edge computing devices increases the surface area for attacks. However, edge computers are equipped with TPM 2.0, which protects the device from physical attacks through authentication and key management.

3. Storage Space

Edge computing requires more storage space than data center servers. However, as solid-state data storage capacity increases and SSDs become cheaper, the edge can have a lot of storage space, thus alleviating the burden of storing all IoT and IIoT data in the data center.

4. Maintenance

Edge computers may require more maintenance than servers, and accessing edge computers is often more difficult and time-consuming than accessing servers. This is because edge computers are distributed, and maintenance may require visiting every location where the equipment is deployed.

Why is edge computing important?

Edge computing is important because it is necessary to accommodate the significant increase in data generated by IoT and IIoT devices. All the raw data generated must be processed and stored, which requires edge computing devices to process and store data locally to reduce the burden on data centers.

Edge computers are like small data centers located near the data generation source. Edge computers can reduce the pressure on data centers by processing and storing data locally, pushing only specific essential data to the cloud. Edge computing differs from cloud computing in that most data is processed and stored locally, and only some relevant or important data is sent to the cloud. This significantly reduces the amount of data that the data center must process or store.

Take the surveillance system as an example. In the old system, all raw footage is uploaded to the cloud for remote monitoring. However, the smart surveillance system is equipped with edge computers to store, process and analyze video clips, and only upload the video clips that trigger specific triggers to the cloud for remote monitoring and control. Sending only some video clips significantly reduces the pressure on the data center compared to sending the entire video clip. Therefore, there is no doubt that edge computing will play a vital role in the future to alleviate the pressure on data centers caused by data explosion.