In this article, you’ll learn what edge computing is, use cases, examples, and how does edge computing work.
What Is Edge Computing?
Edge computing refers to the idea of computing as close to the source of data created and instructions executed as possible.
In simple terms, edge computing is a type of cloud computing in which computing is distributed among devices rather than in a single location on a cloud computing “origin server.”
How Does Edge Computing Work?
Edge computing captures, processes, and analyzes data near the physical location where it is most needed. It significantly reduces the time required to make decisions based on the data, essential for real-time decision-making situations.
Edge computing is more than just one device at the edge; it’s a component of a more extensive network of interconnected locations where data can be processed from the cloud to the device. The location of computing is determined by various factors, including latency, bandwidth, and privacy, all of which are determined by your specific situation.
Most data calculations are now done in the cloud or a data center. However, as enterprises move to an edge model with IoT devices, edge servers, gateway devices, and other gear are needed to reduce the time and distance required for computing tasks and connect the entire infrastructure.
Smaller edge data centers in secondary cities or even rural areas might be part of this architecture, as could cloud containers that can be quickly transferred between clouds and systems as needed.
On the other hand, Edge data centers aren’t the only option to process data. Mobile edge computing employs wireless channels, fog computing, which combines infrastructure that uses clouds and other storage to place data in the most desirable area, and cloudlets, which are ultra-small data centers, are just a few examples.
An edge framework adds the flexibility, agility, and scalability that a rising number of business use cases demand. A sensor, for example, may provide real-time updates on the temperature of a vaccine in storage and if it was kept at the proper temperature during shipment.
Looking at edge computing, you’ll find intelligent refrigerators, smartphones, and self-driving automobiles. Each device can run analytics and store data locally. These devices send data to a nearby edge server or gateway, which coordinates data from the devices, monitors it, and communicates with them.
Furthermore, motion sensors can include AI algorithms that recognize when an earthquake has happened, providing an early warning that allows companies and homes to turn off the gas supply and other equipment that could cause a fire or explosion.
What Is The Use Of Edge Computing?
Edge computing is comparable to Cloud computing in that it enables decentralized storage rather than storing data in a single location, but it also has its own set of advantages. Let’s look at how edge computing differs from other decentralized computing technologies
1. Reduced Latency
When dealing with repeated requests from AI and Machine Learning applications, cloud computing solutions are frequently too slow. Cloud storage will not provide fast and smooth performance if the workload includes real-time forecasting, analytics, and data processing.
2. Working with a limited network connection
Edge computing allows data to be processed locally using in-house processors. It is helpful in transportation since, for example, trains that communicate via the Internet of Things don’t always have a consistent connection during their journey. When they are offline, they can access data from local networks and synchronize activities with data centers once the link is restored.
The edge computing service strikes a mix of typical offline data storage. Data remains within the local network and a fully decentralized approach, in which no data is saved locally.
3. Keeping private data in local storage
Some companies opt not to share sensitive private data with third-party data storage. The security of information is then dependent on the reliability of providers rather than the organization itself. If you don’t have access to a reliable cloud storage provider, edge processing offers a middle ground between traditional centralized and decentralized storage.
Examples Of Edge Computing
1. Advance Maintenance
The performance and uptime of automated equipment are essential in the manufacturing industry. Manufacturing downtime in the automotive industry was estimated to cost $1.3 million per hour in 2006. After a decade of rising financial investment in-vehicle technology and increasing market profitability, unexpected service interruptions have become significantly more expensive.
IoT sensors can monitor machine health and identify indicators of time-sensitive maintenance issues in real-time, thanks to edge computing. The data is examined on the factory floor, and the analytics results are uploaded to centralized cloud data centers for reporting and additional analysis.
2. Oil Rigs
When internet access is scarce, edge computing is the solution for isolated offshore oil rigs. The data generated by oil rigs are more than the networks can manage, and thus IIoT is being used to process it. Edge computing addresses the problem by performing computations in a server closer to the data source, lowering latency.
3. Virtual Assistants
Virtual assistants can analyze data and respond quickly, reducing response time. Instead of communicating with the cloud data center, the virtual assistants use an edge server. Users will benefit from this improvement in reaction time since they will be able to make more timely decisions.
Where is edge computing used?
Edge computing will most likely find applications in a wide range of fields. Consider the medical community: studies are currently underway to employ 5G and mobile edge computing (MEC), combined with artificial intelligence (AI), to find polyps that the human eye would otherwise miss. To detect such anomalies, this preemptive procedure combines the ultra-low latency characteristics of 5G and MEC with the power of AI. In this case, you can enhance existing medical procedures to help save lives.
1. The Internet of Things
The proliferation of internet-connected devices has made the globe hyper-connected nowadays. The internet runs everything from security systems to household appliances and inventory trackers. The creation of edge computing responded to the massive demand for IoT devices.
The importance of interconnectivity cannot be overstated. Consider a smart home: If you connect all of your devices to the internet, you can control and connect all aspects of your life to make day-to-day life easier.
2. Applications in industry and manufacturing
The advantages of IoT devices are already being realized in industry and production. However, with edge computing, they may be able to accomplish much more. Interconnectivity allows for faster construction and more precise inventory management, resulting in increased profits.
Edge computing drives industrial applications, any device or apparatus used in the construction or manufacturing of products. Manufacturing machinery predictive maintenance necessitates near-real-time accuracy. With so many commoditized products today, getting data to customers faster should be a significant difference.
3. Virtual reality, augmented reality, and cloud gaming
Edge computing projections are known to impact the gaming industry significantly. Because applications are close to the end-user, 5G Edge has enabled cloud gaming. The mobile network is also tuned to reduce latency to the edge nodes as much as possible. AR and virtual reality (VR) require ultra-low latency and massive capacity, but these requirements may now be met thanks to edge installations. 5G and edge computing have a lot of potential for improving the user experience.
4. On a higher wavelength
Amazon Web Services (AWS) unveiled its newest edge service, AWS Wavelength, earlier this year, built explicitly for latency-sensitive applications delivered via 5G networks.
Verizon and Amazon Web Services have collaborated to develop Verizon 5G Edge, a mobile edge computing platform that combines Verizon’s 5G Ultra Wideband network with AWS cloud services.
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