By | November 21, 2023
Impact of Edge Computing on IoT

Companies typically have a well-defined strategy for scaling data capacity to meet increasing user and application demands. However, the increasing number of IoT devices transmitting data puts a significant strain on the IT infrastructure.

According to a Statista report, “Number of IoT Connected Devices Worldwide 2019-2023, with Forecasts to 2030,” the number of IoT devices will be more than 29 billion by 2030 globally.

According to a recent report from Accenture, “Leading with an edge: How to reinvent with data and AI”, 83% of companies believe that edge computing will be critical to remaining competitive.

Edge computing enables companies to move computing and storage resources closer to IoT devices. While this reduces the amount of data transferred, it also makes the IoT apps more efficient in delivering higher value.

How is Edge Computing a Game Changer for IoT?

Accenture’s report also states that:

  • Only 65% โ€‹โ€‹of companies use Edge today
  • 81% believe that failure to act quickly could lock them out of the full benefits of technology

IoT devices or systems receive and transmit data over a network. Companies can analyze data in real time using AI or ML algorithms to seek insights from large volumes of data.

Edge computing moves computing, storage and networking functions close to the physical location of data sources. Moving computing services closer to data sources provides more reliable services and a better user experience. In addition, companies can implement new types of latency-sensitive applications efficiently.

Edge computing allows IoT devices to be more independent. These devices can store, process and analyze data locally instead of sending it to the centralized server. While this improves the efficiency of existing IoT devices, it also enables new devices and deployment topologies.

Combining edge computing and IoT makes it easy and flexible to deploy workloads on IoT hardware. This improves performance, reduces latency and offers high throughput data, which is difficult to achieve with traditional IoT.

How does IoT benefit from Edge Computing?

Edge computing benefits IoT by minimizing network traffic and latency. In addition, IoT devices send small packets of data to the central management platform for analysis. Here, edge computing optimizes bandwidth and sends long-term storage data to the central platform, not all data.

In addition, cyber attackers often take advantage of the large volume of connected devices to carry out DDoS attacks. Edge computing’s localized approach makes it easier for businesses to manage security.

Here are some more benefits-

1. Robust data security

IoT devices are an easy target for cyber attacks โ€“ computing can help secure networks and improve overall data privacy. It does this by storing private or restricted data sets in different locations.

In this way, processing power remains limited and is not readily available. In addition, data is distributed between the devices. So hackers will have a hard time taking down the entire network or compromising all data with a single attack.

2. Lower operating costs

When businesses store and process data “at the edge,” businesses don’t need abundant cloud storage. At the same time, edge devices do not require a lot of bandwidth or processing power. Therefore, they are cheaper in the long run.

Companies can use edge servers and devices to store data for as long as needed. They can therefore save data without paying recurring fees or renting cloud storage.

It also enables companies to sift out the unnecessary information and back up only the relevant information. As a result, infrastructure costs will inevitably decrease.

3. Unlimited scalability and better app performance

Edge computing allows companies to scale IoT networks as needed. This makes it easy to keep up with the latest technology and rapid data growth.

As mentioned, it takes some time for the data to travel back and forth between the device and the data center. So, data is stored and processed close to its source. In this way, Edge computing reduces latency and helps improve overall app performance.

4. Minimal latency and network congestion

Many IoT devices are unpredictably dispersed, making it difficult to create an effective network connection without assistance. Furthermore, remote servers cannot handle all these requests because it would create too much traffic on the Internet.

With edge computing, there are fewer problems with server overload. This is because the processing takes place closer to where the data comes from. This facilitates efficient communication between IoT devices without any delays.

5. Lowers energy consumption

Edge computing offers an efficient computing architecture. This architecture helps to reduce energy consumption in a given object or system. For example, edge devices can collect energy and produce power independently using solar panels.

This way, smaller IoT devices don’t have to depend on the power grid, so they consume less energy overall. All these factors make edge computing a more sustainable solution for IoT devices, saving the environment and energy costs.

6. Processes data faster and privately

Data collected by IoT devices is sent to a central system. Data will take some time to reach its destination, causing delays. Edge computing enables data processing that helps complete tasks faster than centralized architectures.

This means that the information can be analyzed at the edge unit itself. In addition, the instructions can be executed in real time, which improves response times.

Edge computing systems can also process encrypted data. In this way, no third party has access to sensitive information. In addition, it also ensures that collected data adheres to privacy standards and industry compliance requirements.

7. Better Quality of Service (QoS)

Edge computing improves QoS by ensuring certain service levels for data that needs to be processed quickly. This ensures that real-time apps receive bandwidth and latency guarantees for a better web experience.

8. Enables faster deployment of software updates

Software updates free IoT devices from bugs. In addition, these devices will also have new security updates, features and other technical changes.

When IoT devices work with edge computing, it becomes easier to detect problems and mitigate their impact. It enables companies to quickly recover from problems, saving time and money on potential damages and recalls.

Also Read: Top Five Edge Computing Trends to Watch Out for in 2024

Why should Edge Computing and IoT come together?

Applying edge computing to the IoT system helps optimize device performance and reduce power consumption. It enables companies to use more complex algorithms safely and securely on an IoT system.

Additionally, it will help predict future outcomes and events. With this future data, IoT devices can become more intelligent and self-sufficient. At the same time, the product or services will become more reliable, leading to increased customer satisfaction and loyalty.

In addition, IoT devices are still relatively expensive due to their specific components, which are difficult to obtain. By decentralizing its functions, edge computing offers more affordable options. It enables companies to explore more ideas in wider business sectors.

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