Methods in data storing and processing always evolve. Therefore, tech companies need to catch up and make sure they are using the most suitable and profitable practice. One option available for them is edge computing.
In the last few years, you may have been familiar with the cloud computing system. You can find it on services like Apple iCloud, Google Drive, or EC2. Those cloud computing services utilize the internet as the main server. Whenever there’s internet available, you can store and process your data using cloud computing services. But, what if there’s no adequate internet connection available? That’s when you need edge computing.
Edge computing allows its user to process the data near where the data source is located, offering faster and instant data streaming. It means you don’t need cloud computing because you can process the data using edge computing. This will reduce data processing traffic from the local server to the cloud server. To know more about what cloud computing is, let’s see the explanation below.
Definition of Edge Computing
The emergence of edge computing dates back to the late 90s. Akamai (a tech company based in Massachusetts) introduced a Content Delivery Network (CDN). It was meant to give faster performances for networks. In CDN, nodes were used to cache web content. Those nodes were also able to perform a limited amount of content customization.
Edge computing basically refers to the process of data collection, storage, and analysis in the edge network, near where the real data is produced. It is different from cloud computing, where data collection, storage, and analysis are being done in the cloud server.
Edge computing is not commonly used yet right now. However, it will become a central part of the technological landscape in future years. This results from the enormous amount of data that have to be processed, most of them coming from increasing the Internet of Things (IoT) devices.
Consequently, this will push the need for much greater data computing and storing ability. Therefore, tech companies will be inclined to invest in edge computing.
The edge computing services will be physically similar to big data centers used by tech companies nowadays. However, it will have the ability to be controlled and maintained remotely.
Perhaps one of the most advanced examples of edge computing you can see in your daily life is a self-driving car. A self-driving car requires an ultra-quick response from the computing device. The data produced by numerous sensors in the device has to be processed immediately by the onboard computer locally with no room for delay.
While processing data locally, a self-driving car also has to receive and process data of the road traffic, nearby events, and weather from the internet.
It is predicted that in 2021, at least 60% of global companies will start to adopt it. They will use edge computing to monitor and process the data of their company using edge computing.
Three Types of Edge Computing
Compute edge is often referred to as a micro data center. It is a small-sized data center, and it consists of several numbers of servers. Compute edge generally located not far from the IoT devices. It is usually related to some local compliance reasons.
A compute edge includes rack-mounted servers complete with cooling equipment. This edge computing device can have a great amount of storage capacity. But, of course not as big as the cloud one. Still, compared to the cloud server, a computing edge has much less latency and a more reliable bandwidth connection.
Device edge is often referred to as a nano data center. It consists of a few servers with a small storage capacity. Device edge is often found in locations that don’t need big data storing and processing capacities, such as cars, factories, or small stores. Because of the light workload, a device edge can work without cooling equipment, unlike a computing edge.
Sensors are devices that are used to collect data. For example, microphones, body sensors, and security cameras. They only have a small capability of doing computing work. Therefore, they have to be connected to data centers like device edge and compute edge to do more complex computing tasks.
Advantages of Edge Computing
According to Statista, there will be 75.44 billion IoT device users in 2025. It means we need a system that can work effectively to support those devices so that they can perform optimally. Experts have stated that edge computing will do the job well. Let’s take a look more in-depth at what edge computing has to offer for us.
The most obvious plus point of edge computing is speed. Edge computing allows devices to respond instantly, maybe even in micro-seconds. If you use edge computing, you don’t need to send the data to the cloud server and receive it again.
Besides having better data transmission speed, the overall end-user experience will be improved because of smaller latency. You don’t have to experience a slow connection problem anymore.
Security and Privacy
Edge computing utilizes the localized data transmission process. Theoretically, your data will be saved, and your privacy can be ensured. There’s a smaller room for a network breach in edge computing.
With a closer and more comfortable-to-each data center, there will be fewer possibilities of you having a problem with the network. Even if there is an unpredictable event like a power outage, the connected IoT devices will still be able to function independently.
This is the most important thing for a tech company. You have to find a way to cut down on resources so that you can earn more profit. Edge computing doesn’t have the need to send data to a cloud server. It means it uses much less traffic in the network. Therefore, it uses fewer resources for the data transmission process.
Companies can harness the latency and energy implications of cloud computing by using edge computing. By distributing the data computation, companies will have to use less bandwidth.
Disadvantages of Edge Computing
Even though it seems to be a better and simpler option for data processing, it actually has some drawbacks. See the list below to know more about the drawbacks.
Bigger Investment Value
Investing in infrastructures for edge computing is costly, and it needs a lot of resources. Edge computing is complicated. Thus, it needs a lot of high-tech tools and experienced manpower to operate. Plus, you also need to put the IoT devices needed into consideration. This can lead to costly investment value. Nevertheless, this is the cost required to have an efficient data computing system.
More Resources in Maintenance
Edge computing is a distributed system, unlike cloud computing, which uses a centralized one. There will be more network combinations, with several data centers in edge computing compared to the cloud one.
Hence, more manpower, time, and money will have to be allocated to maintain and ensure all parts of the network work properly.
The Bigger Need for Storage Space
Compared to cloud computing, edge computing takes a significantly higher storage space on devices. Actually, it is not really a big deal of a problem, considering that companies have produced more compact storage devices. Nonetheless, it is still an important point to be taken into consideration.
Partial Data Processing
Unfortunately, in edge computing, only partial sets of information are processed and analyzed. You may have to make peace because you cannot process all the data you want in this system.
Therefore, please be mindful about what types of data you want to put into edge computing to avoid losing some unprocessed data.
Even though it has been stated above that edge computing has a smaller room for network breach, you can be exposed to greater damage when a breach happens. It is due to the presence of sensitive and essential stored in your data center. The risk is getting bigger every time someone has physical access to your device.
What Skills You Need to Have Before Using Edge Computing
It is essential to strategically recruit and employ skilled manpower in your company to help you operate your edge computing network. Your manpower must have experience in organizing a data center. Your manpower also must have adequate skills in internet security, storage, network, and virtualization.
The implementation of edge computing will not be an easy “plug and play” solution. Keep in mind that in edge computing, the ability to place the right workload on the right device is crucial.
Therefore, you need to employ detailed and skillful manpower to build an efficient and optimally working edge computing network.
How Edge Computing Benefits Businesses
Edge computing can benefit businesses from various kinds of industries. The cost savings alone can be a great selling point. Companies will move towards using an edge computing system.
Edge computing can really help companies in processing a copious amount of data. See some examples of how the implementation of edge computing will benefit companies in the future.
Benefits for Healthcare
Edge computing can benefit healthcare businesses and medical centers in solving latency issues, especially when dealing with medical device management. They can localize their patients’ medical data instead of relying on a centralized data processing center.
Thus, they can provide a faster, more accurate, and more efficient medical response to their patients.
Let’s say that a patient in a hospital uses a wearable device with a local onboard computer to process data locally. The doctors and nurses can monitor the condition of the patient in real-time. They can notice any form of abnormalities faster. So, they can provide a quicker medical decision, and it might save a lot of lives.
Benefits for Retailers
For retailers, the steps of data processing have always been gathering data locally from stores or branches and then processing it in one data center.
Edge computing will enable branches to process their own data locally while still making communication and coordinating with the head office.
It’s can also be considered that edge computing will improve the security aspect of your retail stores. For instance, if your store uses a security camera with a motion-detecting feature, it doesn’t need to continuously stream the data to the cloud server.
Instead, edge computing allows your camera to send the data to a local data center first. Then, the data can be sent to the cloud server on a needed period basis. Retailers can also use edge computing to monitor customer buying behavior.
Benefits for Manufacturers
Manufacturers can start moving into the smart manufacturing era. The ability to perform real-time analysis with edge computing gives an excellent opportunity to achieve better efficiency and bring more margins for the company.
Anything that slows down production or brings a halt can be prevented by monitoring any change or abnormalities in the production line. This ability can save a company from a greater loss caused by a malfunction in the manufacturing plant.
Faster and Better Business Decisions
Overall, edge computing can give numerous benefits for a company, wherever you want to put it into work. It will help leaders in their decision-making process. In the future, companies will rely on real-time data mining to make the best decision.
The Bottom Line
edge computing has offered as many promises. As mentioned earlier, edge computing still faces technical side issues, such as complex maintenance and big investment cost. On the other hand, it can provide us with a more reliable and faster data processing service.
Nevertheless, it still faces many challenges. It still has big potential and much room to grow. Now maybe it is the right time for companies to look into edge computing because, in the next future years, the need for dependable data processing service will be bigger.