What is Edge Computing?
Brian Noble, a computer scientist, demonstrated in 1997 how mobile technology might process data faster than a centralized system using edge computing. By 2001, the term “Edge Computing” had been coined, and the concept was beginning to take hold. Edge computing is a type of computing that brings data storage and computation closer to the users and devices that need it rather than relying on a central server. This can be accomplished by dispersing resources around several areas, including the network’s edge, in order to process data more rapidly and efficiently.
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Why is Edge Computing important?
It is crucial because it aids industrial and corporate organizations in improving operational efficiency, performance, and safety, automating critical business processes, and providing “always-on” availability. It’s a proven strategy for transforming the company’s operations to the digital age. Increasing its capabilities paves the way for autonomous systems and leads to increased efficiency while enabling individuals to focus on higher-value tasks.
The Internet of Things is frequently made in relation to it. Because IoT devices are growing increasingly powerful, most of the data generated can be pushed to the “edge” of the network. This eliminates the need for data to be sent back and forth between a centralized server to be processed. As a result, edge computing is better at managing large amounts of data from IoT devices.
Uses of Edge Computing in Different Sectors?
The uses of edge computing are the following:
Autonomous Vehicles: EC can be used to process the data generated by autonomous vehicles in real-time. This is necessary to make decisions such as when to brake or turn.
AR/VR: It can be used to process the data generated by AR/VR devices in real time. This is necessary to provide a smooth and realistic experience.
Smart Cities: It can be utilized in smart cities to process data supplied by IoT devices in real time. This is required in order to make traffic routing and energy management decisions.
Manufacturing: It is used in the real-time processing of data produced by IoT devices. This is necessary for making decisions, such as when to replace a part of the machine.
Healthcare: it can be used to proceed with the tasks caused by IoT devices. This is required for making judgments like when to refill shelves.
Retail: The data generated by Devices can really be analyzed in real-time using edge computing.
Transportation: The data generated by Smart devices can be handled in real real-time using edge computing. This is required in order to make judgments such as freight routing.
Top 5 Benefits of Edge Computing
Edge Computing has many benefits, including:
1. Reduced latency: It brings compute resources closer to data sources, reducing latency.
2. Improved efficiency: It can improve the efficiency of applications by processing data locally rather than sending it back and forth across a network.
3. Reduced costs: It can save money by reducing the need for expensive infrastructures like data centres and servers.
4. Increased security: It can increase security by keeping data local and avoiding the need to send it over a network where it could be intercepted or hacked.
5. Increased scalability: It can be scaled up or down quickly and easily, depending on the needs of the application.
What are the challenges of Edge Computing?
One of the most difficult tasks is ensuring that Edge Computing systems can handle the large amounts of data generated by devices at the network’s edge. This means that companies need to invest in powerful hardware and software to support their Computing infrastructure. Another issue is supplying sufficient power and cooling for massive computing machines, which are often located in remote or difficult-to-reach areas.
Finally, these systems must be highly available and scalable to meet the needs of future applications. Every person on the planet will be generating 1.7 MB of data every second by 2025, according to estimates. With the advent of 5G and the IoT, this number is only going to increase. This increase in data volume is already putting a strain on traditional centralized data centres, which are not designed to deal with such high volumes of data. It will need to be able to process this data in real-time without any latency issues.
Related Article: Top 6 Edge Computing Applications