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    Home»Computing»Influence of Edge Computing on IoT
    Computing

    Influence of Edge Computing on IoT

    eduardo_alves38By eduardo_alves38November 21, 2023Updated:November 21, 2023No Comments6 Mins Read
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    Influence of Edge Computing on IoT
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    Firms usually have a well-defined strategy for scaling data capacity to meet the increasing user and application demands. However, the rising number of IoT devices transmitting data significantly strains the IT infrastructure.

    As per a report by Statista, “Number of IoT connected devices worldwide 2019-2023, with forecasts to 2030,” the number of IoT devices will be more than 29 billion 2030 globally.

    As per a recent report by Accenture, “Leading with an edge: How to reinvent with data and AI,” 83% of firms believe edge computing will be vital to remaining competitive.

    With the help of Edge computing, firms can move computing and storing resources closer to IoT devices. While this reduces the amount of data transmitted, it also makes the IoT apps more efficient to deliver higher value.

    How is Edge Computing a Game-Changer for the IoT?

    Accenture’s report also states that:

    • Only 65% of companies are using Edge today
    • 81% think failure to act quickly can lock them out from the full benefits of the tech

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

    Edge computing moves computing, storage, and networking functions near the physical location of data sources. Moving the computing services closer to the data sources offers more reliable services and a better user experience. Moreover, firms can deploy new types of latency-sensitive applications effectively.

    Edge computing allows IoT devices to be more independent. These devices can store, process, and analyze data locally rather than send it to the centralized server. While this enhances the effectiveness of the existing IoT devices, it also enables new devices and deployment topologies.

    Combining edge computing and IoT makes deploying workloads on IoT hardware easy and flexible. This improves performance, lowers latency, and offers high throughput data, which are hard to achieve with the traditional IoT.

    How the IoT Benefits from Edge Computing?

    Edge computing benefits IoT by minimizing network traffic and latency. In addition, IoT devices send small data packets 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.

    Also, cyber-attackers often exploit the large volume of connected devices to execute DDoS attacks. Edge computing’s localized approach makes it easier for firms to manage security.

    Here are a few more benefits-

    1. Robust Data Security

    IoT devices are an easy target for cyberattacks- edge computing can help secure networks and improve overall data privacy. It does this by storing private or limited data sets in different locations.

    This way, the processing power remains limited and is not easily accessible. Moreover, the data is distributed among the devices. So hackers will find it hard to take down the whole network or compromise all the data with a single attack.

    2. Lower Operational Costs

    When storing and processing data “at the edge,” firms do not need abundant cloud storage. At the same time, edge devices do not require much bandwidth or processing power. Hence, they are more affordable in the long run.

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

    It also enables firms to sift the unnecessary information and back up only the relevant data. As a result, the infrastructure costs will inevitably reduce.

    3. Unrestricted Scalability and Better App Performance

    Edge computing allows firms to scale IoT networks as required. This makes it easy to keep up with the latest tech 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. This way, Edge computing reduces the lag time and helps improve the overall app performance.

    4. Minimal Latency and Network Congestion

    Many IoT devices are unpredictably dispersed, making it hard to form an efficient network connection without help. Also, remote servers cannot handle all of these requests as it would create too much traffic on the Internet.

    With edge computing, there are fewer issues of server overload. This is because the processing takes place closer to where data originates. This facilitates effective communication between IoT devices without any delays.

    5. Lowers Energy Consumption

    Edge computing offers an efficient data processing architecture. This architecture helps reduce the energy consumed in a given object or system. For instance, edge devices may collect energy and produce power independently using solar panels.

    This way, smaller IoT devices do not have to depend on power grids, so they consume less energy overall. All these factors make edge computing a more sustainable solution for IoT devices, saving the environment and energy expenses.

    6. Processes Data Faster and Privately

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

    This means the information can be analyzed at the edge device itself. Also, the instructions can be carried out in real-time, improving response times.

    Edge computing systems can also process encrypted data. This way, no third party has access to sensitive information. Moreover, it also ensures that data collected adheres to the privacy standards and industry compliance needs.

    7. Better Quality of Service (QoS)

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

    8. Allows for Faster Software Updates Deployment

    Software updates frees IoT devices from bugs. Moreover, these devices will also have new security updates, features, and other tech changes.

    When IoT devices work with edge computing, detecting problems and mitigating their impact becomes easier. It allows firms to quickly recover from issues, saving time and money on potential damage and recalls.

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

    Why Should Edge Computing and IoT Must Go Together?

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

    Moreover, it will help anticipate 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.

    Furthermore, IoT devices are still relatively expensive due to their specific components, which are hard to obtain. By decentralizing its functions, edge computing offers more affordable options. It allows firms to explore more ideas in wider business sectors.

    Check Out The New Enterprisetalk Podcast. For more such updates follow us on Google News Enterprisetalk News.



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