Edge computing cover image

Do you feel the need for real-time responsiveness and lesser latency while transferring data over cloud? If yes, then Edge is your solution. It is the estimation that the edge computing market size can reach $87.3 billion in 2026. The computing environment is moving toward decentralized edge computing networks. This shift is due to the emergence of high-powered devices and improved cellular networks such as 5G. However, what exactly does the term “edge computing” mean, and how does this technology translate into practical applications?

What Is Edge Computing?

Edge computing is a form of distributed computing that involves relocating computations and storage closer to the location where data is created. This location is referred to as “at the edge.” It is a prediction that there would be rapid responses in addition to considerable savings in bandwidth. Rather than being a single technology, “edge computing” refers to overall computer architecture. It’s a type of distributed computing that takes the topology and physical location into account. 

The first commercial edge computing services featured applications like dealer locators, shopping carts, real-time data aggregators, and ad insertion engines as networks adapted to host applications and their components at the edge servers in the early 2000s. 

Today, using the computer resources already present in off-site locations like stores, warehouses, factories, etc., application developers may create use cases like:

  • Decreased delays dramatically
  • Reduced bandwidth requirements
  • Protecting sensitive information more thoroughly
  • Allowing work to continue despite damage to connected systems

Why Is There A Need For Edge Computing?

  • Problem
    • Cloud and AI were supposed to automate and speed up innovation by driving meaningful insight from data, but this has proven to be an elusive goal. 
    • The ability of networks and infrastructure to handle the enormous amount and complexity of data generated by connected devices has been exceeded. 
    • Bandwidth and latency difficulties have arisen as a result of data being transferred to a centralized data center or the cloud. 
    • Due to the exponential rise and rising computational capability of IoT devices, formerly unimaginable data quantities have been generated. 
    • And when 5G networks boost the number of linked mobile devices, data volumes will continue to rise.
  • Solution
    • Edge computing provides a better option for processing and analyzing data at the point of creation. 
    • There is far less latency since data does not have to be sent over the network to a cloud or data center. 
    • Edge computing makes faster and more thorough data analysis possible, especially mobile edge computing on 5G networks, which may lead to better insights, quicker response times, and enhanced consumer experiences.

Components Of Edge

Edge Device

Every day, we interact with various devices that perform edge computing, such as smart speakers, smartwatches, and smartphones. IoT gadgets, POS terminals, robots, cars, and sensors can qualify as edge devices if they can do local processing and communicate with the cloud.

Network Edge

For edge computing to operate, an additional “edge network” is unnecessary. 5G can be useful in this scenario since it adds a new node to the chain connecting end users to the cloud. Autonomous drones, remote telesurgery, smart city initiatives, and much more will all benefit from the low latency and high cellular bandwidth that 5G provides to edge computing. When outstanding responsiveness is required, yet it would be impractical and expensive to install computational infrastructure on-premises, the network’s periphery can be an enormous help. 

On-premises Infrastructure

This hardware can be a server, router, container, hub, or bridge and is used to manage local systems and establish network connections.

Edge makes valuable data more accessible, which paves the way for new opportunities and innovations in the future.

What are the Benefits of Edge Computing Services?

Edge computing solutions offer benefits similar to the cloud’s capabilities but much better. Faster information delivery, more customer satisfaction, and simplified scalability are just some of the benefits for businesses. Let’s dive further into the advantages of edge apps: 

Predictive Maintenance

The adoption of edge computing solutions has been remarkably rapid in sectors where the loss of precious assets might have a catastrophic effect on the bottom line. Companies may now produce reports in seconds instead of weeks because of the rapid speed of edge computing.

Edge computing in the oil and gas sector aids in proactive pipeline management, fault identification, and failure prevention, providing a functioning example of predictive maintenance in corporate computing.

Support For Remote Workforce

Businesses have been forced to relocate employees around the city and the world due to the pandemic. This change in how people work, from being primarily based in an office to being able to do their jobs from anywhere, is a perfect scenario for deploying edge apps. As more businesses embrace the benefits of a distributed workforce, they must find a means to facilitate remote workers’ access to internal networks.

Edge computing solutions can help a dispersed workforce in a few key ways:

  • Minimizing the amount of information the network must carry
  • Assuring both high computational density and adaptability
  • Eliminating redundant information
  • Complying with Mandatory Standards

Faster Response Time

Businesses may greatly aid in reducing latency by placing the computational process near the edge devices.

To illustrate this point, consider the time it would take for an employee on the first floor to send an urgent message to a colleague on the fifth floor if that communication had to go outside the building, interact with a server situated somewhere in the globe, and then return to the first floor. However, a router would be in charge of office data transfers with the aid of edge for corporate solutions, which will drastically reduce latency while conserving bandwidth.

Data Security

Businesses rely on data more than ever today—precisely, information about their company and customers. Currently, processing large data sets is far safer and more efficient when performed close to the data source. This reason is as follows:

  • Cloud computing is convenient for many reasons. However, when organizations keep data in the cloud, it gets stored in one place. Data in one place makes it easy prey for hackers and phishers. With an edge-computing architecture, the data no longer relies on a central location for processing or storing it. Thus, Edge computing adds another degree of protection. It is disseminated to a large number of gadgets.
  • A phishing assault on an edge computing solution’s network can be mitigated by isolating the affected node before spreading throughout the system.

Easier IoT Adoption

Organizational investments in Internet of Things infrastructure continue to increase. IoT has become a valuable tool in the corporate world, especially in sectors that rely significantly on networked equipment. Now, there is a need for the more specialized data center for enterprises that want to increase their computing capabilities to incorporate IoT into their processes.

Businesses may quickly and affordably embrace IoT with the help of edge computing technology since it places no strain on the network. Using the edge computing capacity, businesses may expand into the lucrative IoT sector without investing heavily in new or upgraded infrastructure.

Lowered IT Expense

Business investment in cloud computing is growing across the world. Many people now prefer remote work and the cloud to store and analyze data because of the epidemic.

It is now possible to reduce the cost of transferring data to the cloud. It can be done by storing it closer to the network’s edge. Which is by the way a good news for businesses looking to cut back on their IT budgets. Although, cutting costs is important, but edge computing services can help many ways. Edge computing can assist organizations generate more money by providing the bandwidth and connectivity needed to test new business ideas.

How Does Edge Computing Work?

  • The key to successful edge computing is location. 
  • Data in conventional corporate computing is generated at a user’s local computer and transmitted via WAN (wide area network), such as the internet. 
  • Later it is then received by the company’s local area network, where it is stored and processed by an enterprise application. 
  • The results are sent back to the user when that process is complete. 

For the majority of standard enterprise software, this client-server architecture has been and continues to be the most effective and efficient method.

  • However, traditional data center infrastructures can’t keep up with the exploding number of internet-connected gadgets and the massive amounts of data created and utilized by organizations. 
  • According to Gartner, by 2025, 75% of enterprise-generated data will be created outside of centralized data centers. 
  • Since the global internet is already prone to congestion and disturbance, the notion of transporting that much data in scenarios that can sometimes be time/disruption-sensitive – places great strain on it.

Therefore, IT architects have relocated their attention from the data center to the logical edge of the infrastructure, bringing computation and storage closer to the data source. 

The idea of placing computer resources in the appropriate area rather than relying on a single central location is at the heart of edge computing. It has its origins in remote computing concepts that date back decades, such as remote offices and branch offices. Edge computing places data storage and processing closer to the point of collection. It involves just half of the equipment needed to function on a distant LAN (local area network). 

Challenges Of Edge Computing

Edge computing holds potential for many applications. It’s important to keep in mind that several factors impact the widespread implementation of edge computing. Those factors are beyond the common issues with network bandwidth and are mentioned below:

Limited Capability

The vastness and breadth of cloud computing’s resources and services are major selling points when it comes to edge (or fog) computing. Deploying infrastructure at the edge can be beneficial.However, it is important to define the scope and purpose in well manner.


Though edge computing can get beyond traditional network constraints, even the most lenient edge implementation will need at least some degree of network access. It’s crucial to plan for what will happen at the edge if connectivity drops or is intermittent while designing a deployment for the edge. Successful edge computing requires autonomy, artificial intelligence, and graceful failure planning in the face of connection issues.


It is crucial to design an IoT edge computing deployment that will prioritize effective device management, such as policy-driven configuration enforcement, security in computing, and storage resources, due to the renowned insecurity of IoT devices. While large cloud providers’ IoT services often feature encrypted communications. However, this isn’t always the case when constructing a new edge node.

Data Lifecycle

The fact that most of the data created today are pointless has long been a significant issue. Consider a gadget for monitoring a patient’s vitals: only information about abnormalities is truly important because storing days’ worth of seemingly innocuous readings serves no purpose. In real-time analytics, much of the data is temporary and is discarded after a certain amount of time has passed. After doing an analysis, a corporation must choose what information to preserve and what to delete. It is necessary to secure the data in compliance with corporate and government regulations.

Edge Computing Use Cases And Examples

ManufacturingEdge computing was used by an industrial producer to keep tabs on production, with the use of real-time analytics and machine learning at the factory’s periphery to root out quality issues and boost output.
FarmingEdge computing allows acquiring and analyzing environmental data for optimal crop harvesting in case when consumption of water, nutritional density, and harvest timing are all tracked via sensors. It can reduce planting time by 60%.
Network OptimizationUsing analytics to discover the most reliable, low-latency network channel for each user’s data, edge computing can aid in optimizing network performance for users throughout the internet.
Workplace SafetyEdge computing can integrate and analyze data from on-site cameras, employee safety devices, and other sensors to assist organizations in monitoring conditions or ensure personnel follow safety standards.
Improved HealthcarePhysicians can take rapid action to assist patients avoid health catastrophes in real time with the help of edge computing – for automation and machine learning to access the data, disregard “normal” data, and detect unnecessary data.
RetailEdge computing assists businesses to examine vast troves of information like inventory, sales, etc. to find profitable insights, accurate forecasts of future sales, vendor order placement, etc.

How Is Edge Computing Technology Different From Cloud Computing?

edge computing cloud computing
ScalabilityHigh, Easy to scaleHard to scale
DistanceFar from the edgeAt the edge
Data AnalysisLess time-sensitive data processing, permanent storageReal-time, instant decision making
Computing PowerHighLimited
OperationOn cloud platforms like Amazon, EC2, etc.On device
ApproachProcesses data that is not time-drivenProcesses time-sensitive data
SecurityDoes not require a robust securityRequires robust security and advanced authentication methods

Which Are The Top Edge Computing Companies?

The top edge computing service providers with the reasons why we think these companies are:

Amazon Web Services

AWS solutions focus on various fields, including artificial intelligence (AI), the internet of things (IoT), analytics, and more. Their cloud-edge paradigm offers a unified interface.


They can provide orchestration and administration services for edge computing through the use of their OpenManage Mobile capabilities.


They have recently developed an Edge Native Intelligent Asset Application. ClearBlade did so to make it easier for users to establish a link between the enterprise’s main computer system and the Internet of Things device.


With the growth of IoT and the introduction of 5G, the technology of the future, edge computing, has attracted attention. Now that you are aware of the advantages of edge computing versus cloud computing, it is time to put them into practice. Contacting the leading edge service providers for businesses is essential for the quickest implementation of edge computing capabilities within the enterprise. In order to help you incorporate new technologies into your project and business, Idea Usher is here to help.

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What exactly is edge computing?

Edge computing is a technique for bringing the cloud’s data and processing power closer to the location where data is generated. The technology enables enterprises to shift the data processing and result delivery process closer to the data’s original source. Examples of edge computing in the real world include self-driving automobiles, facial recognition software, etc.

Why do businesses use edge computing?

There are several commercial use cases for edge computing:

  • It reduced IT costs
  • Deliver greater responsiveness
  • Support remote workforce
  • More secure data, etc.

What are the uses of edge computing?

There is a tonne of real-world applications for edge computing, including:

  • Autonomous vehicles
  • Remote equipment and asset monitoring
  • Cloud gaming and in-hospital patient monitoring
  • Delivery of content
  • Managing processes and inventory in retail, etc.

Who can be the user of edge computing?

Network administrators and systems integrators need edge computing to swiftly join devices across IoT networks and improve system performance and data management.

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