Edge Computing vs Cloud Computing: The Difference

The concept of edge computing is nothing but computing in a highly distributed environment. This consists of storage and computing power closer to the computer where it is quite essential for the sources of information. When it comes to cloud computing, data is routed through separate data centers, but the data is not scanned; rather the cloud comes as a help to all. There is significant savings in storage space and delay.

If we compare with IoT technology, edge computing can be used as an alternative method for the computing fraternity. This is about having access to real-time data, extremely close to the data source, which is called the “edge” of the channel. Instead of having a secure cloud or database server or a data storage facility, it’s all about having virtual machines closer to where the data is being generated.

For example, in the case of a vehicle measuring fuel consumption, there are sensors that provide data and then there are sensors that rely exclusively on the data provided. The machine that performs this program is known as an edge computer system or literally – an edge device. As we can observe this change in the acquisition and management of data, we will look at the details of these two computer techniques and also delve into some of the merits that each of these techniques must provide.

What is edge computing?

Using a unified computing infrastructure along with a broadcast channel, various computing resources and communication technologies can be easily deployed. This is only possible due to edge computing. By taking advantage of the use of edge computing, businesses can easily meet the requirements around computer science.

With edge computing, whenever it is necessary to collect information or for a particular user to perform a specific activity, the same can be done on a real-time basis. If we want to know the main advantages of edge computing, then improved efficiency and reduction of operating costs are the two primary ones that are related to edge computing. However, let’s also look at some of the other benefits of edge computing.

(Read on to Know More: What is Edge Computing? ‘Everything You Need to Know)

Advantages of edge computing

  1. Security

    While there have been the emergence of various IoT technology-based edge computing devices, and an increase in potential network attack vectors, there are many security benefits that edge computing can demonstrate. If we look at the conventional cloud computing model, then it is primarily centralized. This makes the whole arrangement vulnerable to exploitation. With a variety of devices and cloud services, edge computing spends computer and storage solutions and various applications. This makes it very difficult to eliminate an isolated case.

  1. Fast

    One of the significant advantages of edge computing is its ability to improve the productivity of networks by reducing any type of latency. The data stored does not have to travel long distances, unlike the traditional cloud environment. This is because IoT edge computing devices can manage private data by accessing nearby edge data centers.

    For many businesses, speed is becoming critical. For example, the financial services industry cannot have any latency. Having even a millisecond of delay can create a significant impact on the business. Another situation is the health sector. One cannot imagine the serious impact on people’s lives if there is a spit in the machinery and equipment that runs the sector. Organizations working on a customer-centric model may face customer anger if they do not get the desired experience due to slow speed. Thus, speed becomes a critical factor for businesses.

  1. Performance improvement

    Edge computing is not just about collecting data. It also analyzes and performs necessary actions on the collected local data, in addition to the data that is required to be transmitted to the cloud. Even if these tasks are performed in a fraction of a second, it is still critical because it has a direct impact on the performance of the systems.

    For example, in the case of industrial plants, if these tasks are carried out by isolated plants, then it may present an obstacle to the transmission of large volumes of data in real-time mode. However, this issue is addressed by tagging spy tools and applications with the network edge. Using edge computing, analyzers can be brought closer to the machine, thus eliminating the broker.

  1. Reduction of operating costs

    When we consider elements such as performance characteristics, traversal, data management, and communication, cloud computing turns out to be a very expensive option. However, edge computing has a very low bandwidth demand and much lower bandwidth consumption, making it an extremely cost-effective option.

  1. Scalability

    It is not easy for businesses to anticipate IT infrastructure requirements and the investment of having a dedicated private cloud instance will be excessive. Therefore, edge computing provides a flexible option for scaling up.

  1. Reliability

    Having IoT-enabled computing devices along with cloud network infrastructure, which is close to and available to end users, reduces any risk of network failures or network problems in a remote location.

Use cases of Edge Computing

There are multiple examples where edge computing is used, however, the three main areas where edge computing is widely used are

  • Distributed / OTT
  • Automotive / AI powered vehicles
  • Smart Homes

What is Cloud Computing?

A simple definition of cloud computing is the use of different users over the Internet. These resources include application frameworks, storage systems, servers, and other software as well.

There are three main functions that every cloud service provider will deliver.

  1. Flexible services
  2. The cost of various services involving memory, preparation and bandwidth must be borne by the user
  3. The entire back end of the software is managed and managed by the cloud service providers

(Read on to Know More: Cloud Computing | Ultimate Beginner’s Guide)

Cloud Computing Service Models

From a market point of view, cloud computing models can be deployed in different types, depending on the requirement. The different cloud computing service models are:

  1. Platform-as-a-service (PaaS): PaaS customers can access the platform and thus implement the software and cloud applications. Things like internet connectivity and operating systems are not in the user’s control. This may result in some limitations on the scope of the software. Some of these examples are Amazon Web Services, Rackspace, Microsoft Azure
  2. Software-as-a-service (SaaS): SaaS this model, the right to access or use the cloud service, also known as a cloud-hosted application, must be provided by the user.
  3. Infrastructure-as-a-service (IaaS): IaaSthe client can manage and control the operating systems, software, network access and storage without managing the cloud itself.

Deployment models in cloud computing

Like virtualization techniques, cloud computing also has a set of prerequisites that are necessary for successful deployment. There are mostly four types of deployment models in cloud computing.

  1. Community Cloud
  2. Private Cloud
  3. Public Cloud
  4. Hybrid Cloud

Advantages of Cloud Computing

Although we talked about some of the challenges presented by cloud computing, earlier in this article, however, there are a few key benefits that the model delivers.

  1. Flexibility
    The model is flexible because it allows organizations to start small and then grow faster. The best part is that climbing up and down is very easy making the whole model easy to operate.
  2. Coherence
    Cloud service providers are responsible for both system security delivery and the data recovery process.
  3. Mobile Access
    Cloud service ensures that users are connected seamlessly with mobile applications
  4. Maintenance
    In the cloud computing model, the cloud service providers ensure the maintenance of all the applications and services they provide.

Difference between Edge Computing and Cloud Computing

Now that we’ve seen what these two computer methodologies have to deliver, let’s do a quick comparison check to see the inequality between the two.

Differentiation factors Edge Computing Cloud Computing
Scheduled Multiple application programs can run at different types during development. The Cloud computing model uses a single programming language for the specific development of applications on cloud platforms.
Security This requires a very thorough and comprehensive security standard, with complex authentication methodologies. Cloud computing does not require extensive security.
These organizations Applications that have a considerable bandwidth problem can go for edge computing, making it a viable and optimal choice Any application that is involved in a large amount of data processing can be done using cloud computing.
Operations The computing process takes place on the system itself. Mostly on the system itself, edge computing takes place. Here, the storage of applications takes place on the cloud server, such as Amazon EC2 or Google Cloud.
Advantages A new machine can be connected to a network by building the network. Much of the data can be stored on the cloud server and then accessed over the Internet.

Leave a Reply

Your email address will not be published.