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Edge Computing vs. Cloud Computing: What's the Difference

Introduction:

           Cloud Computing and Edge Computing are two concepts in the modern digital world. Both are the growing concepts for storing data on Cloud. In this blog, we first go through the terms Edge Computing and Cloud Computing. Later, we discuss the advantages along with disadvantages of Edge and Cloud Computing in detail. In the end, we go through the fundamental difference between Edge and Cloud Computing.

Edge Computing:

Edge computing is a way of doing computing and storing data closer to where it's needed, instead of sending it far away. In data center or some central location, data processing occurs closer to the source of the device generating the data. As a result of edge computing, latency and bandwidth requirements can be reduced when there is a requirement to transferring large amount of data to the processing center. Edge computing allows real-time decision-making by processing data close to the edge and accelerating data transfer to and from the cloud.

IoT devices, automated vehicles, and AR/VR-augmented reality/virtual reality systems are the ones most dependent on the benefits of low latency, especially with edge computing. 

Advantages of Edge Computing:

Speed

  • It makes the data travel a shorter distance and gets it to its destination faster.
  • It helps avoid slowdowns and long waits on the network.
  • Edge computing boosts speed and improves overall service quality. 

Low latency

  • It skips sending data to the cloud and back, so everything happens faster and responds in real time.
  • It keeps heavy tasks close to the user, so things happen faster. This helps make quick decisions and makes using the service better.

Lower costs

  • It reduces the amount of bandwidth needed.
  • Use edge devices instead of data centers.
  • Reduce data storage requirements.

Cloud Computing:

Cloud computing means using the internet to access and use IT services, like storage and applications, instead of having them on your own computer or server. Instead of regular servers, storage, databases, OS, and applications, users can offer shared pools of reconfigurable computing resources while expelling the need to know about maintaining the underlying infrastructure

                        Cloud computing has revolutionized the way organizations and individuals acquire computing resources and access them. They can share computer resources provided by a cloud operator, such as Amazon Web Services, rather than buying and maintaining their hardware and software. This brings scalability, cost savings, increased agility, improved reliability, and global access.

Advantages of Cloud Computing:

1)      Cost Savings

2)      Security

3)      Flexibility

4)      Scalability

5)      Reliabilit

Difference between Edge Computing and Cloud Computing:



 

             Parameter

 

Edge Computing

 

Cloud Computing

 

 

 

Defination

 

Edge computing is a system that moves computing and data storage closer to where the data is created.

 

Cloud computing is a way to provide IT services and resources over the internet.

 

 

 

Location of Processing

 

Processing happens right at the edge of the network, close to the device that creates the data.

 

 

Data analysis and processing happen at a central place, like a data center, rather than at the location where the data is created.

 

 

 

Bandwidth Requirements

 

Low bandwidth is needed because data is processed close to where it’s created, reducing the need to send large amounts of data over long distances..

 

 

Higher bandwidth is needed compared to edge computing because data has to be sent over the network to a central location for processing.

 

 

 

Costs

 

Edge computing can be more expensive because it often needs special hardware and software at the edge.

 

 

 

Cloud computing is cheaper because users only pay for the resources they actually use.

 

 

 

Scalability

 

Scaling edge computing can be tougher because you might need to add more computing resources directly at the edge.

 

 

It's easier to scale up or down because users can quickly adjust their computing resources as needed.

 

 

 

Use Cases

 

 

Applications that need quick responses and real-time decisions include IoT devices, self-driving cars, and augmented/virtual reality systems.

 

 

 

Applications that don’t need fast response times include web apps, email, and file storage.

 

 

 

Data Security

 

Data security can get better because the data is processed close to where it’s created and doesn’t need to be sent over the network.

 

 

Data security is trickier because the data has to travel over the network to a central location for processing.

 

Author Bios :

v  Mrs. P. Valarmathi (M.Tech)

v  Mr. R. Premkumar (M.E)

v  Sree Hari S, IV-CSE

 

 

 

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