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what is Edge Computing and How does it work?

Edge Computing

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Do you recall the 1st ever huge and bulky sets of computers? As devices grew smaller over the years, their computing and processing powers have expanded exponentially. While data warehouses & server farms were once appraised to be the ultimate choice for computing speed, the focus has swiftly shifted to the notion of cloud or “offsite storage”. 

Companies like Netflix, Spotify and other companies have even built their entire business models on the concept of cloud computing. Nevertheless, cloud computing comes with a number of drawbacks. The biggest problem of cloud computing is latency because of the distance between users and the data centres that host the cloud services. This has led to the development of a new technology called edge computing that moves computing closer to end users.

In this article, we will explore the concept of edge computing in detail, and explain how it offers many excellent advantages, importance of Edge computing, how it works and many more details.

What is Edge Computing?

Basically, edge computing refers to the concept of computing as near as possible to where data is created and commands are executed. This form of computing could likely be on the client device itself such as a mobile phone, surveillance camera, drone, or autonomous vehicle or it might be performed a few hops away, such as on a locally connected server next to a cell tower or in a small, local data center. The prime takeaway is that edge computing is done as geographically or intellectually close to the source of the information as possible, in order to lessen network traffic and latency. 

This is done when 5G communications & cloud computing may already be ubiquitous, as the time it takes to send a request to the main server and get a response may still be too long, especially for time critical tasks, like steering an autonomous vehicle. An acceptable edge device, whether it is an edge server or a potent client device, will be able to circumvent the obstacles and difficulties of latency, bandwidth, and response time. 

In circumstances where privacy or security can be a difficulty, edge computing may also be preferable. Modern examples of the next wave of smart technology, such as artificial intelligence and the Internet of Things, rely heavily on the deployment of edge devices.

This trend is expected to carry on for quite some time. According to the market research firm IDC, by 2023, more than half of newly established enterprise IT infrastructures will be deployed at the edge rather than in central data centres. The market research firm Gartner forecasts that up to 75 percent of enterprise generated information will be built and processed at the edge of the network by 2025.

Edge Computing
What is Edge Computing and How does It work?

How does Edge Computing Work?

In a traditional setting, details are produced on a user’s computer or any further client application. It is then moved to the server through channels such as by the internet, intranet, LAN, etc., where the information is stored and worked upon. This remains a classic & proven approach to client server computing. 

However, the exponential growth in the volume of data produced and the number of devices connected to the internet has made it difficult for traditional data centre infrastructures to accommodate them. The concept of edge computing is simple: instead of getting the data close to the data centre, the data centre is brought close to the data. The storage and computing resources from the data centre are deployed as close as possible to where the data is generated.

Benefits of Edge Computing:

Edge computing has emerged as one of the most worthwhile solutions to network obstacles associated with moving huge volumes of information generated in today’s world. Here are some of the most prime benefits of edge computing:

1. Eliminates Latency: Latency refers to the time needed to transfer data between the 2 points on a network. Large physical distances between these two points combined with network congestion can give rise to delays. As edge computing brings the points near to each other, latency issues are virtually unreal.

2. Saves Bandwidth: Bandwidth refers to the rate at which information is transferred on a network. As all networks have a finite bandwidth, the volume of data that can be transferred & the number of devices that can process this, is limited too. By establishing the data servers at the points where data is generated, edge computing enables numerous devices to operate over a much smaller and more well organised bandwidth.

3. Reduces Congestion: Although the Internet has expanded over the years, the volume of data being produced each and everyday across billions of devices can give rise to a high level of congestion. In edge computing, there is a local storage & local servers can accomplish essential edge analytics in the event of a network blackout.

Edge Computing
Edge Computing

Drawbacks of Edge Computing: 

Although edge computing provides a number of benefits, it is still a fairly new technology and a long way from being foolproof. Here are some of the most notable drawbacks of edge computing:

1. Implementation Costs: The costs of implementing an edge infrastructure in an organisation can be both complex and expensive. It requires a distinct scope and purpose before deployment as well as supplementary equipment and resources to function.

2. Incomplete Data: Edge computing can only process limited or incomplete sets of data which should be distinctly defined during implementation. Due to this, companies may end up dropping valuable data and information.

3. Security: Since edge computing is a dispersed system, ensuring ample security can be challenging. There are risks involved in processing information outside the edge of the network. The addition of new IoT devices can also grow the opportunities for the attackers to invade the device.

Cloud vs Edge Computing:

Cloud and edge computing are similar by their key purpose, which is to avoid storing data at the single centre and instead distribute it among multiple locations. The main difference is that cloud computing prefers using remote data centres for storage, while edge computing keeps making partial use of local drives. Edge computing also uses remote servers for the majority of stored information, but there is a possibility to decide what data you’d preferably leave on the drive.

Edge computing is a superb backup strategy in the following scenarios:

  • The network does not have adequate bandwidth to send files to the cloud data centres.
  • Business owners are uncertain about retaining sensitive details on remote storages, where they have no power over its storage & safety standards;
  • If the network isn’t always well founded, edge computing offers smooth access to files even in the offline mode.
  • Applications need fast data processing, this is especially usual for AI and ML projects that deal with terabytes of data daily. It would be a waste of time to run each and every file by data storage when an edge application offers an instant response from the local network.

Realistically, edge computing wins over Cloud in all cases where communications tend to be unsteady. When there is a chance that a connection will vanish, but there is still a need for real time data, edge computing provides a solution. Cloud computing, additionally, has its own unique benefits that can be bounded by the edge’s attachments to the local network.

  • No entail to invest in securing local networks: If the company does not have established security practices & a professional support team, arranging local storages to accommodate sensitive edge details and information will require a lot of time and resources.
  • It is easier to store large datasets: Edge computing is great if companies don’t require to save all the data that they collect. But, if insights are supposed to be stored long term, local networks will not be actually able to accommodate huge data sets on a daily basis sooner or later, the information would have to be deleted. This is why most large data projects use Cloud: as it allows storing large amounts of information with no limitations, even if it needs the sacrifice of the computing speed.
  • Easy to deploy on various devices and software: Data, stored on the cloud, is not limited to specific hardware. Provided that a user has an Internet connection, the data can be accessed any time and from any device, as soon as the access requirements are met.

Edge computing focuses on providing firm and fast performance across the whole enterprise. It can not store large amounts of information because local networks have size limitations, but the presentation is smoother.

Edge Computing
Edge Computing
Examples of Edge Computing companies:

Global technology players have united with the edge computing trend a long time ago. There are already numerous services that can be used by enterprises to execute edge computing in their data storage. Let’s take a look at edge computing use and projects that are being implemented by big organisations.

Siemens: The company launched the Industrial Edge solution, the platform where manufacturers can analyse their machine’s data and its workflow instantly. The non essential data is transferred to the cloud, which lessens latency on the local network.

Crucial bits are stored at the edge of the network regionally, on the hardware. If there is an issue with a net connection, industrial companies can still retain track of their productivity, detect technical problems, and prevent downtimes.

Saguna: It’s an edge computing provider that provides an infrastructure for edge computing implementation. The company built Open-RAN, the set of tools that aid build, deploy, and secure edge computing stores. The tools enable companies to set up low latency data transfers and secure sensitive data.

ClearBlade: It uses the Internet of Things and edge computing to enable enterprises to set up edge computing across various devices. If a vacation or business has a ready IoT edge device, developers can transfer it to edge storage through using Clear Blade’s development and security tools.

Cisco: It provides a set of communication tools for implementing edge computing, compatible with 4G & 5G connectivity. Businesses can connect their services to the Cisco Network Service Orchestrator to store data, collected by their software, on the edge of the local network and Cisco’s data centres.

IBM: IBM’s IoT platforms and Artificial Intelligence tools support edge computing as one of many possible computing options. Presently, the company’s research is focused on building networking technology that joins multiple edge networks with no WiFi connections.

Dell EMC: It has been actively investing in the Internet of Things ever after the opening of an IoT division in 2017. The company now adapts edge computing to store information from its IoT edge devices. Dell developed a custom set of specialized instruments: Edge Gateways, Power Edge C-Series servers, and others.

Amazon: It has already proven to be one of the most firm and powerful cloud computing providers. AWS is the finest cloud solution on the market presently. It’s common that the company takes an interest in edge computing as well.

Microsoft: Microsoft has the potential to revolutionize edge computing the way Amazon revolutionized the cloud. The company presently holds more than three hundred edge patents and invests in developing various IoT infrastructure. The most prominent instance is their IoT Azure service, a package of tools and modules for executing edge computing in IoT projects.


The demand for automation and the internet of things keep growing, and devices need to deal with real-time data and produce immediate outputs. When industries like healthcare and autonomous transportation began investing in automation, new data processing challenges arose.

Even a second of delay can make a life-or-death difference and lead to multi-million economic and reputational damage. Under such conditions, it’s imperative to have a reliable data processing technology that can answer offline requests and deliver prompt responses.

Shifting data storage from cloud data centres closer to the network allows reducing operation costs, delivering faster performance, and working with low bandwidth. These benefits can potentially solve multiple issues for healthcare, AI, AR, any field and technology that requires fast real-time data processing. You can implement edge computing into your enterprise operations right now and access these benefits. It’s possible with an experienced tech partner who knows how to set up data transfers, secure local networks and connect systems to edge storage. To know the facts about Edge Computing that one can’t ignore, Click Here.

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