Learn more about how edge computing can reduce latency, increase performance, improve data security, and more.
The modern business landscape constantly works with data generated in large amounts by computers, applications and IoT (Internet of Things) devices, making data the heart of every business transaction.
As more computing devices are developed and introduced into businesses, it is expected that larger amounts of data will continue to be generated, stored and processed worldwide. The International Data Corporation (IDC) global datasphere forecast for the period 2021-2025 indicates that global data generation will continue to increase.
With this expected surge in data volume, there is a general concern that organizations will struggle to reduce data processing latencies and inefficiencies. This is where edge computing comes in. Edge computing enables companies to optimize their systems by offloading data processing to the sources where the data is created, rather than depending on data centers to process and analyze data.
There are several edge computing benefits that organizations can leverage to create a robust and efficient system and we will uncover some of them here.
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What is edge computing?
Edge computing is a computing model that places key processing tasks within the framework or environment in which data was generated. It is a framework that supports the generation, storage and processing of data in the place where it is created, without resorting to a data center or centralized data processing environment.
This computing framework eliminates the need for data collected from endpoints to be sent back to centralized data services for processing and analysis. Rather, data is processed immediately in the same environment in which it was created.
Edge Computing Benefits
Hosting applications and data on centralized hosting platforms or centers can introduce latency when users try to use them over the internet. Requesting data from these data centers can become slow when there are internet connection issues. Edge computing solves this problem by keeping data at the edge of devices for easier access.
Therefore, with edge computing, organizations can avoid issues that affect speed and connectivity because data can be pulled on the endpoints, rather than from a distant central data center and then back to the endpoints. By reducing the time it takes an application to retrieve data from a data center, applications remain optimized for better performance and a better user experience.
Improves privacy and data security
Data security and data protection are hot topics in the IT world. Edge computing offers more data security and privacy because data is processed within the edge and not by central servers.
However, that doesn’t mean that edge devices aren’t vulnerable at all. Not at all. It just suggests that there is less data to be processed by the edge, leaving little to a complete collection of data for hackers to dig into.
In other words, privacy can easily be compromised when data hosted on centralized servers is hacked as it contains richer information about people, places and events. On the other hand, since edge computing creates, processes, and analyzes only one set of data needed in an instance, other pieces of data that could compromise privacy in the event of a hack are not tampered with.
Reduces operating costs
Moving data through cloud hosting services is one of those things that companies spend a lot of money on. The higher the volume of data moved on these centralized hosting providers, the more money companies spend.
However, with edge computing, companies spend less on operational expenses because data only needs to be minimally moved to the cloud. In addition, because the data is processed in the same place where it is generated, the bandwidth required to handle the data load is reduced.
Helps meet legal and compliance requirements
Meeting legal and compliance requirements can be complicated when data is hosted and managed by different data centers or hosting providers. This is because each data center has its unique privacy and regulatory requirements.
However, this is not the case with edge computing, as data is created, stored and processed in one place, making it easy to meet regulatory and compliance requirements.
Improves reliability and resilience
With edge computing, data can still be accessed and processed with little or no obstacles even when there is an internet connectivity issue. Additionally, failure of one edge device does not alter the operation of other edge devices in the ecosystem, improving the reliability of the entire connected system.
Supports AI/ML applications
There’s no denying the growing importance of artificial intelligence (AI) and machine learning (ML) in modern computing. However, AI/ML applications work by fetching and processing massive amounts of data, which can lead to latency and connectivity issues when the data is hosted on a central server.
In contrast, edge computing facilitates AI/ML applications because the data is processed close to where it originates, making it easier and faster for AI/ML to produce results.