Edge computing refers to data processing at the periphery or edge of a network — as close to the original data source as possible. It’s a distributed IT architecture, often compared against a centralized cloud computing architecture. For instance, a typical smart speaker command usually needs to be processed in the cloud. That’s why users experience a noticeable lag between when they ask the smart speaker something and when they receive a reply. Now that can be frustrating, but similar lag in a self-driving car can be fatal. In an enterprise, by Placing computing power closer to the sources of data — aka routers, wide area network devices, and IoT devices — Edge Computing makes it so the data has less distance to travel, and more places to travel to, than in a monolithic and distant cloud infrastructure.

Edge computing eases the strain on resources by processing data close to the source and only sending valuable data to a remote data center. For instance, a smart thermostat will only transmit data if the temperature rises or falls outside set limits. Similarly, a security camera will only transmit data if it detects motion.

Edge computing:

  • Improves time to action,
  • Reduces response time down to milliseconds,
  • Conserves network resources,
  • Reduces data bottlenecks,
  • Enables 5G connectivity, among many benefits.

Edge computing won’t completely replace cloud computing. Some notable cons of edge computing include:

  1. Security Challenges, as its distributed architecture, means more possible attack vector
  2. Licensing Costs, which may negate edge computing’s initially low ticket price
  3. Configuration Challenges, as administrators may inadvertently create security holes across each individual edge device or create configuration drift.

Edge computing has been primarily driven by the expansion of IoT and is necessary for 5G, since 5G relies on a multitude of network nodes with weaker frequency bands that can only travel short distances.

What are Edge Computing | 5G | Futureyan

Proper Definition of Edge Computing:

Edge computing and FoG computing are huge buzzwords at the moment. So, I want to try to explain what they are it basically means instead of collecting data on your phone and sending it to a server far away to be analyzed you perform the analysis on your device. So, Apples fingerprint recognition is a great example of their facial recognition so if I want to use face ID or fingerprint ID, I simply put my fingerprint on it and the phone will use the artificial intelligence of machine learning to recognize it.

We now perform more and more calculations on devices because our chips are computer chips within them are becoming more powerful and this is enabling there’s a whole new world where Internet-connected devices make more decisions and process more data.

A good example is CCTV camera so if we record like in a home security camera for example in the past we would link these security cameras up to a live stream and this would then record this somewhere on a server and it would recall this 24 hours a day and for the vast majority nothing happens and every now and then someone turns up and the camera records it but the camera is not intelligent enough it will just record and the processing will take place somewhere in the cloud on a server somewhere far away.

Modern-day security cameras actually have this intelligence build in so they know that nothing is happening here, so I actually don’t have to send this data anywhere I will only record the bits when something is happening when there’s movement when someone’s turning up and this is the power of each computing that is actually more of the computing activity and the intelligent processing takes plays on the edge where the device sets in the camera on your phone and it reduces the bandwidth that we need we don’t need to send petabytes of data back to a cloud server we can only send us the bits of information we really need so this is Definition of edge computing.

What is edge computing in simple terms?

Edge computing refers to data processing at the periphery or edge of a network — as close to the original data source as possible. It’s a distributed IT architecture, often compared against a centralized cloud computing architecture. For instance, a typical smart speaker command usually needs to be processed in the cloud.

What is edge computing with example?

Edge computing refers to data processing at the periphery or edge of a network — as close to the original data source as possible. It’s a distributed IT architecture, often compared against a centralized cloud computing architecture. For instance, a typical smart speaker command usually needs to be processed in the cloud.
A good example is CCTV camera so if we record like in a home security camera for example in the past we would link these security cameras up to a live stream and this would then record this somewhere on a server and it would recall this 24 hours a day and for the vast majority nothing happens and every now and then someone turns up and the camera records it but the camera is not intelligent enough it will just record and the processing will take place somewhere in the cloud on a server somewhere far away.

What does Edge Computing do?

Edge computing and FoG computing are huge buzzwords at the moment. So, I want to try to explain what they are it basically means instead of collecting data on your phone and sending it to a server far away to be analyzed you perform the analysis on your device. So, Apples fingerprint recognition is a great example of their facial recognition so if I want to use face ID or fingerprint ID, I simply put my fingerprint on it and the phone will use the artificial intelligence of machine learning to recognize it.

What is the difference between cloud and edge computing?

Cloud Computing refers to computing services such as data storage or computing power or programs that are provided on demand and are delivered as a service over the internet. While Edge Computing moves the processing of data closer to the source of where the data is produced, it moves it away from the cloud in an effort to optimize systems.


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