Harnessing the Power of Edge Computing in Cloud-Based IoT Solutions

Ravi Jadhav
Published 08/03/2023
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The IoT landscape is constantly expanding. Ranging from POS devices to HVAC, lighting dishwashers and machinery, IoT is changing how humans live and operate. In fact, it has a significant influence on businesses. These solutions have a unique performance standard that you don’t have to worry about latency and buffering. IoT operates from the cloud, but we all know that the cloud has performance and connectivity issues.

However, with time, organizations are becoming more dependent on technology-centric devices and edge computing because it improves efficiency as they can process huge amounts of data at the edge. So, let’s see how edge computing can be leveraged for cloud-based IoT solutions.

Understanding Edge Computing

This is a computer paradigm, so the computation can happen on the data source or closer to it. It’s different from the conventional approach of using the cloud as the primary computing place. However, it doesn’t mean that cloud will instantly vanish either. In simpler words, the cloud will be approaching you. It plays an important role in improving the performance of online apps.

That’s because it tends to bring processing closer to its data source. It can discard the need for long-distance connections between servers and clients, which helps lower the consumption of bandwidth and latency. It can improve online apps as well as internet devices because data processing will be closer to the data source.

Working of Edge Computing

In the past few years, the majority of organizations have started migrating their important data and apps to the cloud. It also includes data from sensors, which are installed in the production units because it helps collect insights. In addition, it makes sure that equipment is managed remotely. On the contrary, IoT sensors are gaining popularity, which leads to data growth.

It can stress out the central cloud servers, and in many cases, it can suffocate the capacity of the network. For this reason, edge computing is used because it can bring computer devices closer to IoT devices. To develop a cloud edge, the operators leverage multiple data centers rather than using one cloud data center.

The cloud edge allows different applications by nearing the computation, such as autonomous driving, remote 3D modeling, and cloud gaming. This is essential because all these applications need low latency, so edge networks have become a priority. Edge computing has become a go-to choice because it can process data near the data source, which lowers bandwidth costs as well as latency.

Benefits of Edge Computing

It’s common for everyone to know that edge computing can help minimize latency for time-sensitive apps and improve efficiency in low-bandwidth solutions. In addition, it can help streamline the network performance for resolving network issues. However, we are sharing the benefits of leveraging edge computing in detail!

Low Latency

When the data processing happens locally instead of at a faraway cloud or data center, it will reduce the time-to-action. This is because it’s about physical closeness. Having said that, since data storage and processing happens around the edge devices, the mobile, as well as IoT endpoints, will be able to respond to crucial information in a quick manner.

No Network Congestion

Edge computing can help with wide-area networks when it comes down to coping with increasing traffic. When you reduce bandwidth consumption, you will be able to save money and time. It’s one of the most important barriers in the computing and IoT world. So, instead of adding too much raw data to the network, the edge devices will help filter, process, and compress the data locally.


The edge computing standards help IoT devices in different situations, including when the network isn’t stable. For instance, it can help in the case of remote military facilities, power facilities, and offshore oil rigs. In fact, even if the cloud connection isn’t very stable, the local resources can help keep the ground running.

When edge computing is used, only relevant data will be processed and transmitted to the cloud, which reduces the volume of raw data. The optimization of data will help minimize the consumption of bandwidth and reduce stress on the network. These factors help increase efficiency and cost-effectiveness.

Offline Usage

Edge computing allows IoT devices to operate even when the cloud connection is impacted. That’s because when the data is processed locally, the edge devices will keep operating automatically. As a result, there won’t be any interruptions in the operations or functionality. Once the cloud connection is restored, the data can be synced with the cloud.

Improved Security & Data Privacy

Everyone uses cloud and IoT devices for security, but cloud computing helps increase security standards. That’s because sensitive data is processed locally, so you don’t have to worry about security risks associated with data transmission. Moreover, organizations will have better control over data processing and processing. Also, they will be able to comply with the regulations associated with data privacy and security.

Cost Optimization & Scalability

It’s pretty challenging to optimize cloud resources, but edge computing is a great resource for optimizing cloud structures. In addition, it can reduce costs by offloading computing tasks to advanced edge devices. In simpler words, it helps distribute the workload between the cloud and edge, so organizations can easily scale the IoT solutions without worrying about efficiency and cost-effectiveness.

Centralized Management

The cloud-based IoT solutions have centralized management, data storage, and monitoring. Having said that, edge computing helps optimize the data processing at the edge, so it can send relevant insights to the cloud. In addition, it can help with long-term visualization, analysis, and storage. It will help create a comprehensive overview of the cloud and IoT ecosystems.

Real-Time Analytics

Edge computing promises real-time analytics, so organizations can make decisions right at the edge. Also, local data processing and analysis empower businesses to take quick actions without worrying about centralized processing and the cloud. It’s a promising choice for time-sensitive applications, such as healthcare monitoring and automation. So, it’s promising when it comes down to reliability.

The Bottom Line

Edge computing might be a new trend in the IT world but it’s already making leaps and bounds. The implementation of edge computing on IoT and cloud solutions promises security, efficiency, and reliability. Having said that, it’s time organizations start leveraging it!


Disclaimer: The author is completely responsible for the content of this article. The opinions expressed are their own and do not represent IEEE’s position nor that of the Computer Society nor its Leadership.