Unleash The Power of Edge Computing to Improve Sustainability

Jun 17, 2022
5 min read

Today, businesses of all sizes have the flexibility to place their networking or storage assets outside their cloud environments. They can even place these assets to suit their business requirements, enabling them to deploy applications at edge sites and wherever their business's core value chain is located.

Realizing the potential of edge computing in recent years, businesses started to adopt it to enhance their business results to grow exponentially and be competitive in the ever-changing market.

Edge computing deploys the computing resources outside the data center, where a series of joint assets such as IoT components link the edge device to applications. The paradigm shift in execution practices eliminates edge-computing resources from the protective physical, access, and network security umbrella the data center offers. Edge overcomes the risks of networking capacity and problems concerning infrastructure architecture.

Edge computing technology plays an essential role in the following areas:

Improved Security - Security is considered to be a primary element when deploying edge computing. The closely coupled data arrangements near the sensors make the assets very secure. A complete solid security pack is essential from the sensor to the data center to reduce security attacks.

Interoperability - Edge computing execution differs concerning sensors, devices, and connectivity. Enterprises need to be partnered with a trustable service provider to execute the endpoint sensors and merge and safeguard them to the cloud.

Continuous Support –As the geographical expansion of Datacenters is diverse and rapid, maintenance becomes more challenging. Ongoing support for edge computing is required with automation to ease the job.

Edge Computing For Business Transformation

Businesses that don't consider edge computing need to understand how it can benefit them. If your company wants to stay competitive, it needs to adopt a modern computing infrastructure. Electronic devices such as smartphones, tablets, and laptops have become ubiquitous. As a result of their ubiquity, it is now expected that business processes and transactions run on these devices. However, these devices are not the right fit for some types of tasks requiring an edge computing solution.

Rapid Value-driven Business Outcomes

Organizations are looking for ways to reduce the time needed to collect and analyze data. Edge computing may provide a solution. In addition, the effective use of an edge computing system can provide customers with new capabilities and benefits. Sensitive data can be stored at the edge and does not require any processing or storage in the cloud. The advantages of using edge computing are numerous, with potential uses in security monitoring and data analysis. Some examples include:

• Higher performance than cloud systems

• Lower costs than cloud systems

• Greater safety than cloud systems since devices outside the network core are not accessible to hackers

• Faster speed of access and response compared to cloud systems

• Greater scalability than cloud systems since the information from the edge devices is directly available to servers in real-time. This can be used for a variety of data processing and analysis. As a result, the edge devices can provide information for sophisticated algorithms and machine learning capabilities.

• Cyber-security monitoring is a significant part of an edge computing solution. Since the edge is closest to the devices, it is easier to detect any potential vulnerability associated with that device

• Data analysis is also a crucial part of an edge computing solution. For example, using edge computing and advanced analytics, autonomous vehicles can automatically generate alternative routes to avoid heavy traffic on the road

• In terms of remote surveillance systems, an edge computing solution can allow for better live streaming and recording of remote information for security purposes

Organizations can use edge computing solutions to analyze traffic and use this information to calculate the best routes.

Higher Resilience with Distributed Edge Networks

Some organizations may have facilities at a higher risk for occasional connectivity interruptions due to their remote locations or heightened security. In any organization, sudden connectivity failures can result from bad weather, natural disasters, or unforeseen issues with third-party providers.

Some of the processes involved in an edge computing solution involve specific hardware, software, and network devices. For example, advanced analytics is often associated with hardware such as commodity GPUs. These hardware components capture large amounts of data that requires processing for use by machine learning algorithms. In addition, data aggregation and monitoring can be performed automatically using some software components.

An edge computing solution requires a network device with software components that can directly or through a proxy provide real-time communication with the cloud. These network devices would be placed at the perimeters of the cloud and would provide:

  • Access to specialized hardware and software
  • Capturing data efficiently
  • Analyzing
  • Giving feedback to end-users

Even in such scenarios, edge computing can help the organization enhance its infrastructure resilience and application availability.

Edge Is The New Business Model For Innovative Solutions

Modern companies face ever-evolving challenges when navigating through innovation in security protocols. With the perfect IT platforms and management solutions, edge computing can help them meet their expectations more efficiently. However, IoT networks and edge deployments present new challenges for network operators. These network deployments are often disconnected from the traditional corporate backbone, presenting new regulatory compliance challenges. The rules that apply to your conventional wired or wireless networks should not necessarily be applied to IoT and edge networks because there are significant differences in the technologies used.

Artificial Intelligence for Edge computing

AI has the potential to change the way organizations operate. As computing shifts further towards the edge, it makes sense for AI to move there as that's where the data is. The more processing power, the better. That's one reason big tech companies like Facebook, Apple, and Google are building data centers closer to population hubs. But another trend is also emerging: Companies are also placing their data at the periphery of networks where they can connect to the internet 'edge' to take advantage of more powerful processors and lower latency in deploying artificial intelligence-driven services.

The challenges are too much data and wireless congestion. The problem is that the bulk of the data will move to the edge, putting strain on cellular networks and causing problems for a wireless world built for people moving bits between computers. This is where 5G comes in.

5G should change everything by shifting the power balance from mobile networks to endpoints. This will allow devices to serve as gateways rather than simply act as mobile networks' edges.

The promise of IoT is that devices, sensors, and other endpoints will be able to communicate directly with each other. But the reality is that most IoT applications require connectivity with the backbone.


The data is processed at the edge of an internet or intranet in edge computing. As a result, there is less latency and more security while retaining cloud-like flexibility. It also eliminates the need for high bandwidth interconnects with remote data centers. In addition, edge computing's decentralized approach to cloud computing provides more security and privacy since data doesn't have to pass through a network of third-party storage providers to reach its intended recipient. As a result, adopting an edge computing transformation strategy now appears to provide enterprises with the most incredible level of versatility moving forward.