The technology market is advancing faster and faster in terms of processing and connectivity of devices and cloud applications. However, some items, such as communication latency and dependence on a good internet connection. Become obstacles for technological evolution to occur even more quickly. To meet these needs, the concept of Edge computing arose, which aims to process data in the physical location or close to the data source. The aim of this new architecture is to generate faster and more reliable services. Follow our post and check out the advantages and challenges of this technology called Edge computing.
Edge computing arose from the need to deal with the demands for traffic and data processing, which are increasingly large. Its function is to optimize the use of devices connected to the internet. Reducing the need to pass data over long distances between them and a server, reducing latency and demanding less bandwidth on the internet.
Included at the edges of the networks. These elements process urgent or priority requests and select data that should be sent to the cloud. Minimizing the total data traffic sent to a switch. Examples of devices include smart cars. Which need to process data and make decisions in near real-time, and augmented and virtual reality technologies. Whose slowness or delay in processing disrupts the immersion experience.
Edge computing technology has become essential. As the trend is that there is an increasing number of devices connects by the internet of things, generating congestion in the bandwidth that can be critical in some situations.
In this solution, after local processing. The most frequently used data is stored locally. Data that is stored for lengthy periods of time is sent to the cloud.
Because it is store locally, this architecture reduces the risk of exposure to confidential data and brings greater control over your traffic. Thus, companies are able to reduce the contact surface for attacks and data theft. Preventing breaches of regulatory policies, such as the GDPR and LGPD.
As benefits, we can also highlight the resilience, reduction of failures and delays in the transmission of the service. Since maintaining computing locally allows the operation to occur independently, even when interruptions occur in the main network. The cost of bandwidth for data transmission between facilities is reduce. As processing is close to the source.
There is also a reduction in communication latency, which reaches hundreds of milliseconds. As online services are deploy closer to users. In addition, this architecture has the possibility of enabling dynamic and static caching features, which for end-users results in a faster and more consistent experience. For companies, this reflects in low latency and high availability applications with real-time monitoring.
One of the biggest difficulties is the highly distributed scheduling. Which for small businesses, can be difficult to manage the indirect costs of decentralized processing. In the event of a failure in this remote infrastructure. Some type of user support would be require.
Even though the solution generates greater control over information flows by limiting data geographically, the “physical security” of these edge computing points is generally less. That is, there is a trade-off of greater security in the cloud and in traffic and data for less security in physical devices, which end up becoming more vulnerable individually.
Edge computing technology tends to grow more and more. Despite having some challenges in its implementation, it is a great gain for companies as a way to improve their data processing. Also you can find more helpful resources at worldbeautytips.
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