The Definitive Guide to Edge Computing

Jul 15, 2021
4 min read
“The next phase of our modernization is developing into a data-driven world”

Your own a small organization that suffices with a few CCTV cameras. Think about when it will expand. You will need thousands of CCTV cameras for monitoring. The quality will suffer from increased latency issues and you’ll also have huge expenditures just on the CCTV cameras.

The industries are exponentially expanding. Due to the limitations in bandwidth, disruptions in the network, and latency issues, the traditional computing methods on centralized data centers and the daily internet won’t work well.

This is where edge computing comes to play.

With the growth of augmented reality, self-driving cars, robotics, artificial intelligence, smart cities, and automation, we are diving into the limitless pool of data, for which we need huge processing power and instantaneous responses.

What is Edge Computing?

Edge computing reduces the data amount in centralized or cloud storage by moving a portion of storage closer to the data source. It solves the issues in performance and latency by localizing data and canceling the gap between data storage and computation.

Edge computing is changing the way we handle, process, and deliver information from millions of devices around the globe. world. It allows the work to get done in the same place where the data gets generated.

So, when your organization has CCTVs with edge computing, it will deliver the best performance with negligible latency. Not only your cameras, but you can also include everything, from your sensors to the IoT coffee machine in your office.

How Does Edge Computing Work?

Edge computing works on the concept of distributed computing models, which isn’t new. Having remote and branch offices for data storage and processing is an old custom with a proven record.

The primary goal of edge computing was to reduce bandwidth costs and network congestion. This would drive the growth of real-time applications and IoT devices that entail local processing and storage for advancement in technology.

Edge computing differentiates data by filtering and processing critical and non-critical data, and sending only the non-critical data to the cloud, and analyzing data in the same place or near the network edge.

Edge computing isn’t just about storage, since several applications are time-sensitive. A distributed computation framework brings applications closer to data sources or resident edge servers.

Why Is Edge Computing Preferred Over Traditional Computing?

In traditional computing methods, the data produced at the client’s endpoint is moved across physical data centers for storing data. After processing, the results get conveyed back to the client endpoint.

But devices connected to the internet and the information produced and used are growing too quick for traditional computing to assimilate.

But getting data closer to the data centers isn’t possible. So, IT architects focused to get the data center closer to the data, hence developing edge computing.

Benefits of Edge Computing

There are several benefits of opting for edge computing.

· It does the computation work locally, mostly on the edge device itself, providing autonomy.

· It processing raw data locally and conceals or secures sensitive data before sending it to the cloud servers or main data center, allowing data sovereignty.

· It produces faster insights and reduces latency that proves useful in delay-intolerant applications.

· Implementation of edge computing results in cost savings.

· It provides better bandwidth availability and reduces congestion in the network.

· It acts as the decentralized extension of the site, cellular, or data center networks, or the cloud server.

· It supports distributed computing to bring computation and the storage resources closer, preferably in the physical location same as the data source.

Applications of Edge Computing in Industries

Edge computing has formed the forefront of several industries:

Edge processing acts like an enabler for time-sensitive applications. It keeps the computational power for automated processes coordination of heavy machinery on a factory floor close to the proximity.

In agriculture and farming, farmers can use edge computing to collect data on soil fertility, temperature sensors, weather prediction, and the best tractors from IoT devices.

The instantaneous data insights will help them generate a better yield and warn them about incoming harsh weather conditions that might affect the crops.

Edge computing can help retailers to create a unified store management application. It helps them analyze and use targeted promotions, tracking foot traffic, and identify business opportunities like an effective marketing campaign, sales prediction, and optimize vendor orders.

With time, the data on patients collected from IoT devices, sensors, and other medical equipment has gained explosive growth. The huge volumes of data need edge computing to apply automation and machine learning.

It helps in filtering critical and non-critical data to identify the root problem so that the doctor takes immediate action and prevents health incidents in real-time.

Self-driving cars are the best examples that integrate edge computation in their system. They need and produce anywhere from 5-20 TB every day.

Automated cars need real-time analysis and gathering of data it is in motion about the location, nearby vehicles, speed, vehicle, road, and traffic conditions.

Edge Computing Challenges

Although edge computing has a lot of potentials, it isn’t foolproof yet. Here are a few challenges that it needs to overcome.

· The best edge deployment will need a minimum level of connectivity.

· The scope and purpose of the edge deployment must be visibly distinct.

· Decentralization is a challenging process that needs high levels of monitoring and control.

When data gets handled by different devices, it might not be as secure as centralized or cloud servers. It might need data encryption, employing access-control methods, and VPN tunneling.

· Each device has different processing, power, and connectivity requirements that can impact the edge device’s reliability.

· It should have redundancy and failover management to ensure that the information gets delivered and processed properly.

Edge Computing Possibilities: What’s Next?

Predications from Gartner showed that 75% of data in organizations will be created outside of central data centers by 2025.

Edge computing continues to progress through novel technologies and practices to enhance abilities and performance. Its availability is the most significant trend and they are expected to become available to the entire globe by 2028.

The evolution of wireless communication technologies like 5G accelerated the growth of edge deployments and it will uncover new areas that are yet to be discovered.

Edge computing is the ultimate key to reshaping the IT industry and business computing.