Edge Computing A-Z: A Quick Guide

With huge amounts of data being stored and transmitted today, the need for efficient ways to process and store this data is becoming increasingly important. This is where edge computing comes in – we can improve performance and reduce latency by providing processing power and storage closer to the sources of data generation. Edge computing can help us meet our ever-growing data needs while reducing costs. This blog discusses the importance of edge computing, its pros and cons.

What is edge computing?

Edge computing is a distributed computing paradigm that brings computation and data storage closer to where it is needed to improve response times and save bandwidth.

It’s about placing resources physically closer to users or devices — at the “edge” of the network — rather than in centralized data centers. Edge computing can be used in conjunction with fog computing, which extends cloud computing capabilities to the edge of the network.

Edge computing examples

There are many potential applications for edge computing, including the following:

Connected Cars: Mobile edge computing can be used to process data from onboard sensors in real time, enabling features such as autonomous driving and real-time traffic monitoring. Industrial Internet of Things (IIoT): Edge network computing can be used to collect and process data from industrial sensors and machines in real time, enabling predictive maintenance and improved process control. 5G: Cloud edge computing will be crucial to enable the to support the high bandwidth and low latency requirements of 5G networks.Importance of Edge Computing

Edge computing can help improve many aspects of an organization:

The primary meaning of edge computing is to reduce latency and improve performance by bringing computation and data storage closer to the devices and users who need it, sending it over the network to centralized servers. Edge computing can be used in conjunction with other distributed computing models such as cloud edge computing and fog computing. When these models are used together, they can create a more flexible and scalable system that can better handle the demands of modern applications. How does it work?

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Edge computing can be viewed as a complement or extension of cloud computing, the main difference being that edge computing performs these calculations and stores this data locally rather than in a central location.

Edge network computing nodes are often located at the “edge” of networks, meaning they are close to the devices that generate the data. These nodes can be deployed on-premises or in a colocation facility. They can also be embedded in devices such as routers, switches, and smart sensors.

The data generated by these devices is then processed and stored locally at the edge node. This data can be analyzed in real time or transmitted to a central location for further processing.

What are the benefits of edge computing?

The following are just a few of the benefits of edge computing:

Increased efficiency: Edge computing can make networks more efficient. When data is processed at the edge, only the data needed is sent to the central site instead of sending and filtering all data to the central site. Security Improvements: Cloud edge computing can also improve security. By processing data locally, sensitive data can be kept within the network and away from potential threats. Latency Reduction: Edge computing can help reduce latency. Processing data at the edge of the network, close to the data source, means data doesn’t have to be sent back and forth to a central location, which can take time. What are the disadvantages of edge computing?

A disadvantage of cloud edge computing is that it can introduce additional complexity into the network. This is because data needs to be routed to the appropriate location for processing, which may require additional infrastructure and management.

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Additionally, edge computing can also be less reliable than centralized processing as there may be more points of failure.

Another potential downside to edge computing is that it may only be suitable for some applications. Examples include applications that require real-time processing or are particularly sensitive to latency.

Why is edge computing more secure than centralized processing?

Edge computing is more secure for a number of reasons.

First, data is stored and processed at the edge of the network, closer to the data source. This reduces the time it takes for data to be transferred and the likelihood of data being intercepted. Second, data is processed in a distributed manner, which means that if one node in the network is compromised, the rest of the network can continue to function. Finally, the rest of the network can continue to function. Edge computing systems are often designed from the ground up with security in mind, with security features built into the hardware and software.Edge vs. Cloud vs. Fog Computing vs. Grid Computing

There is no one-size-fits-all answer as to what type of computing is best for any particular organization. It depends on the specific needs and goals of the organization. However, some general trends can be observed.

Businesses are increasingly moving towards cloud computing as it offers many advantages in terms of flexibility, scalability and cost-effectiveness. Edge computing is also growing in popularity because it can offer faster data processing and improved security. Fog computing is another option to gain traction. Fog computing offers many of the benefits of cloud computing but with lower latency. Grid computing is typically used for high-performance applications where large amounts of data need to be processed in parallel.

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Edge computing comes with numerous security challenges that cybersecurity professionals need to be aware of to keep their IT infrastructure and systems secure. As IoT devices grow at an unprecedented rate, so does the way data is analyzed and transmitted. As a result, IT and security professionals must adopt the latest best practices to protect their edge computing infrastructure.

Edge computing in C|EH v12

EC-Council’s C|EH v12 certification equips participants with the knowledge and skills needed to understand, design, and implement solutions for edge computing systems. Learn about the latest commercial hacking tools and techniques used by hackers with C|EH. The modules also cover common security threats and vulnerabilities related to edge computing systems, mitigation and countermeasures.

Ready to advance your cybersecurity career with the C|EH? Learn more!

About the author

Ryan Clancy is a writer and blogger. With more than 5 years of mechanical engineering experience, he has a passion for engineering and technology. He also loves to bring the technique (especially the mechanics) to a level that everyone can understand. Based in New York City, Ryan writes about all things tech and tech.