Cloud computing is increasingly seen as the IT technology of the future. There is almost no company left that does not have at least one application in the cloud these days. However, cloud computing has proven to be inferior to so-called edge computing in some areas. What this is and how your company can also benefit from it, we reveal in the following guide.
The name edge computing describes pretty well what this technology is all about. Instead of being located in a central location, data is processed at the edges of the network. As a rule, this is where the data is collected. At first glance, this technology seems to contradict the principle of cloud computing, where all data is collected, analyzed and made available centrally.
With edge computing, on the other hand, the data is used directly where it is collected. This means that a vehicle sensor, for example, no longer sends all its data to the cloud or a central server, but instead only feeds it into the edge computing system. There, the data is read out and categorized. Only the data that can really be used is forwarded, and this already in compressed and analyzed form.
Edge computing is becoming increasingly important, especially due to the Internet of Things and Industry 4.0. This is because, compared to conventional centralized solutions, data can be read out more quickly and reliably and then also passed on to a central system more quickly and at lower cost. Edge computing is regarded by experts across the board as one of the key technologies for the Internet of Things.
At first glance, it seems contradictory, after almost all data is collected, synchronized and made accessible in clouds, to now split up and decentralize this process again. However, there are good and important reasons for using edge computing.
Ever-advancing digitization has forever changed not only our personal lives, but also the business world. If companies can use the new technologies properly, then digitization usually has far more advantages than disadvantages. Probably the most important advantage is that companies can now access unprecedented amounts of user and customer data.
More data means more knowledge about one's own customers and their consumer behavior, which in turn leads to a competitive advantage. So it's no wonder that corporations and companies around the world want more and more up-to-date data to optimize their own decision-making processes.
However, this data must first be analyzed. After all, the majority of digitally collected data remains worthless. An autonomously driving car, for example, generates 4 TB of data per day - but only a fraction of this is usable by developers. The key, then, is to find and use the right data quickly enough.
Since almost all companies are already using cloud computing in one way or another, as mentioned earlier, the obvious solution was of course to use cloud computing to analyze the data: Through various applications, the cloud can thus collect data, read it, and then make it available to any cloud participant.
The problem with collecting data in a centralized system is that all the data from the respective sensors has to be transmitted unfiltered to the central system, evaluated there, and then the corresponding instructions for action have to be sent back to the appropriate place.
There are several difficulties in doing this: First, the central location is usually simply too far away geographically to be able to avoid long latency periods - regardless of the available computing power. In addition, the transmission of such data volumes requires high-performance Internet connections, which cost a lot of money. Lastly, transferring so much useless data can quickly overload important computing systems.
Especially when a company needs to utilize massive amounts of data, conventional centralized systems such as the cloud quickly reach their limits. And this is exactly where edge computing comes in. Since the data is processed directly at the point of origin, useless data can already be sorted out here. The central system then only receives the important data that is actually usable. In this way, important computing systems can deliver results much faster.
In addition, edge computing allows important instructions to be carried out directly as soon as the data is available and not only when a central system gives the instruction. This is particularly important in medicine, for example. In addition, edge computing naturally saves massive amounts of money by reducing the amount of data that has to be transmitted and the distances over which it has to be transmitted.
Both edge and cloud computing offer countless benefits to users. And with Fog Computing, you can combine the best of both worlds. With Fog Computing, the individual edge computing applications are centrally controlled, while the applications and data exploitation itself still takes place locally. So you can still access all the data from anywhere, while having a system that is efficient enough to actually process that data.