Why does Edge Computing matter?


The fast development of inter-connected technologies such as the Internet of Things (IoT) and 5G wireless has led to unpreceded volumes of complex data. Edge computing helps businesses to manage and process data throughout the world.

Edge computing is then a distributed computing framework that enables data to be analyzed quicker and more efficiently, allowing more opportunity for insights, faster response times, and improved customer experiences.

Hence, we have talked to experts in the industry to learn more about edge computing and what the future holds for it.


What is Edge Computing?

Data in this era is the most valuable asset and with the digital revolution, data is being generated in high volumes at very high velocity, according to Ali Saeed Khan, Head of Engineering. Processing this raw data into useful information is the challenge of the present and future. Data is acquired through millions of devices ranging from handheld devices to microcontrollers.

Carrying this data to a centralized location creates network dependability. One way to handle this challenge is to grow the network infrastructure with the growth in data acquisition. The other way is to bring the processing unit closer to the data. Hence, he continues, the term edge computing is tossed where we bring the processing unit closer to the network edge i.e., end of the network.

The concept of edge computing is thus based on the divide and conquer approach, where we divide the processing units into smaller parts and once the data is processed into information, that information is sent to the centralized storage unit for later use. Edge computing is a set of computational components deployed closer to the data acquisition device(s).

Dalia Adib, Practice Lead at STL Partners, adds that edge computing brings the capabilities of the cloud close to the end-user or end-device. There are debates around edge computing vs fog computing. In reality, the two have similar objectives. A small difference is that fog computing can include running intelligence on the end-device and is more Internet of Things (IoT) focused.

Edge can exist on customer premises, on a Raspberry Pi, in a regional data center, or in a network operator’s facility.

Moreover, Paul Ridgway, Founder of The Curve notes that Edge Computing involves running usually small, low power, often low cost compute devices at a location where computing needs to happen, rather than centrally in some data centre. It can be a device collecting data and sending it somewhere for consumption, for instance, a pollution sensor on a lamp post.


Edge Computing vs Cloud Computing

Cloud is a broader term at a larger scale than the edge, Ali states. Indeed, a cloud consists of different types of resources provided to end-users as a service. These resources range from software to hardware.

Ali underlines that both of these terms should not be compared because both works in tandem to improve the user experience and performance of information delivery. Edge computing can be used in the cloud to reduce the network load. It adds to the overall cost and reliability of the cloud but at the same time makes it more robust and scalable.

According to Paul, Cloud computing is very different from Edge Computing. Cloud Computing is generally the ability to scale up and down compute resources in a provider’s data center without long-term ownership commitments, capex, etc.

Dalia also emphasizes that edge computing is not independent of the cloud. It is often an extension of the cloud to a location outside of hyperscale data centers and part of a distributed compute continuum. As cloud computing is a catalyst for industrial transformation, edge computing should be a key part of the Industrial Internet of Things (IIoT) planning to enable and accelerate digital transformation.

Similar to the cloud, she continues, edge cloud is flexible and scalable. Unlike static, on-premises servers, it has the capacity to handle sudden spikes in workloads from unplanned increases in end-user activity. It also helps scale when testing and deploying new applications, so it is a great solution for enterprises. Besides, efficiency and scalability can be cost benefits for businesses as well.


Is Edge Computing important?

For Ali, edge computing is the future. IoT and IIoT have become the new norm of the way we live and our industries manufacture. With these sensing devices working around the clock, it is impossible to handle the volume of data generated by them. Edge computing is the first answer we came up with, and we have still a lot to cover. Hence, edge technologies will become a component of regular cloud infrastructure.

Edge Computing unlocks new ways of capturing and processing data due to the often small size, low power, and solid-state nature of the devices that can be deployed, Paul says. For some businesses, Edge Computing is an enabler for new ways of working. For instance, one of his clients is using edge computing in their MachineLink product to collect data from CNC machines with a plug-and-play experience for the end-user.

Moreover, Dalia notes that edge computing has the potential to accelerate enterprises’ existing digital transformation by allowing them to access innovative applications while complying with existing processes and data privacy concerns. This can include manufacturing companies using edge computing to allow industrial tools and machinery to be controlled using standard software on standard infrastructure, rather than be tied to proprietary technology. An interesting use case to bring this to life would be automated guided vehicles (AGVs).

Today, she continues, they are designed to run on a set track, which means that when the production line has to change, it requires sufficient time and costs for the operations teams to re-engineer the line and the associated AGVs. Controlling AGVs using software and connecting them over standard networks will allow for flexibility and enable manufacturers to innovate more quickly.


Benefits & Drawbacks 

Edge computing incorporates the benefits of both local computing, such as on the premises, and cloud computing, Dalia points out. The advantages of edge computing include customers being able to run low latency applications better, as well as cache or process data close to the data source to reduce backhaul traffic volumes and costs.

On the other hand, like cloud, edge compute should offer flexibility and scalability. Edge computing can provide the capacity to handle sudden spikes in workloads from unplanned increases in end-user activity or address enterprises’ need to scale quickly when developing, testing, and deploying new applications. For mobile applications, telco edge compute not only needs to scale up and down, but also move across different telco edge locations.

For Paul, Edge Computing can unlock new sources of data, ways of working, and in turn products and services that were otherwise not possible.  There is also a great potential to distribute and decentralize workloads distributing any failure risk.

According to Ali, edge computing offers the following benefits to the cloud over a traditional cloud architecture:

  • Improved Network Performance
  • Distributed Nature, decentralization of data makes edge enabled clouds more secure
  • Scalability
  • Autonomous data collection, the edge devices don’t require a user to power up or log in. These devices are collecting and processing data continuously
  • Reliability, as the devices are decentralized the failures are also less impactful

However, as with any digital transformation, there are always costs to implementing new technology, Dalia notes.

Indeed, the challenge with edge computing is that it’s rarely going to be plug-and-play. It will often need an ecosystem of solution providers to provide each part of the value chain: hardware, software enablers, end applications, and services to support the enterprise with setup and ongoing operations. Besides, the remote devices can be difficult to communicate with and manage remotely, Paul states. In some cases, you may deploy a solution that you can’t then get to so the software and hardware must be very robust.


The future of Edge Computing

Dalia, like Ali, believes that edge is still at a very early stage so it will take time for end-customers to learn about what it is, the benefits and begin implementing it. Early adopters are conducting POCs and starting to scale implementations across sites. But in time, others will follow, and we will see more applications for edge grow in the next few years.

Paul also expects Edge Computing to grow in its use and usefulness. Hardware is becoming cheaper, more powerful, more reliable, and more robust and the same is happening with connectivity like 4G/LTE/NB-IoT. Technologies such as computer vision can now run on edge-type devices and that sort of signal processing unlocks even more possibilities.


Special thanks to Dalia Adib, Paul Ridgway, and Ali Saeed Khan for their insights!