Learn more about how edge computing can reduce latency, boost performance and improve data security among other benefits.
International Data Corporation (IDC) global datasphere forecast covering 2021–2025 suggests that global data generation will continue to surge.
With this expected high-rising volume of data, there is a common fear that businesses will struggle with how to reduce latency and inefficiencies in data processing. This is where edge computing comes to play. Edge computing makes it possible for businesses to optimize their systems by moving 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 businesses can tap into 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 where data was generated. It’s a framework that supports the generation, storage and processing of data in the location where it is created without resorting to a data center or central data computing environment.
Under this computing framework, there is no need for data gathered from endpoints to make it back to centralized data services to be processed and analyzed. Rather, data is processed immediately within the same environment they are created.
Benefits of edge computing
Hosting applications and data on centralized hosting platforms or centers can create latency when users try to use them over the internet. The process of requesting data from these data centers can get slow when there are internet connectivity issues. Edge computing solves this issue by keeping the data on the edge of the devices for easier access.
Therefore, with edge computing, businesses can avoid issues affecting speed and connectivity, as data can be fetched on the endpoints rather than from a far away centralized data center, then back to the endpoints. Reducing the time an application travels to fetch data from a data center keeps applications optimized for better performance and greater user experience.
Enhances privacy protections and data security
Data security and privacy protections are burning issues in the IT world. Edge computing provides more data security and privacy protection because data is processed within the edge rather than from central servers.
However, this does not suggest that edge devices are not vulnerable by any means. Not at all. It only suggests that there is less data to be processed from the edge, so there is hardly a complete collection of data that hackers can pounce on.
In other words, privacy can easily be compromised when data hosted on centralized servers are hacked because they contain more comprehensive information about people, locations and events. In contrast, because edge computing creates, processes and analyzes just a set of data needed at an instance, other pieces of data that might compromise privacy in the event of a hack are not tampered with.
Reduces operational costs
Moving data around on cloud hosting services is one of the things businesses spend a lot of money on. The higher the volume of data being moved on these centralized hosting providers, the more money organizations spend.
However, with edge computing, organizations spend less on operational costs due to the minimal need to move data to the cloud. In addition, since data is processed in the same location it’s generated, there is also a reduction in the bandwidth needed to handle the data load.
Helps in meeting regulatory and compliance requirements
Meeting regulatory and compliance requirements can be made more difficult when data is hosted and managed by different data centers or hosting providers. This is because each data center has its peculiar privacy and regulatory requirements.
However, this is not the case with edge computing because data is created, stored and processed in one place, making it easy to meet regulatory and compliance requirements.
Enhances reliability and resiliency
With edge computing, data can still be fetched and processed with little or no hindrances, even when there is a poor internet connectivity issue. In addition, when there is a failure at one edge device, it won’t alter the operation of other edge devices in the ecosystem, facilitating the reliability of the entire connected system.
Supports AI/ML applications
There is no denying the growing relevance of artificial intelligence (AI) and machine learning (ML) in modern computing. However, AI/ML applications work by fetching and processing huge volumes of data, which can suffer latency and connectivity issues when the data is hosted on a centralized server.
In contrast, edge computing facilitates AI/ML applications because data is processed close to where it’s created, making it easier and faster for AI/ML to obtain results.