Reviewing the Shift from Internet of Things (IoT) to Edge
There is a rapid growth when it comes to the amount of data being produced by digital devices. The conventional model of data processing and storage in the cloud costs plenty of resources, and often, it is not fast enough to meet the needs of the end user. As a result, organizations are switching to an alternative approach – one that can process data closer to IoT devices.
According to Gartner, traditional data centers use the cloud to create and process 10% of enterprise-generated data. Gartner expects that this figure will increase to 75% by 2022. This shift to edge computing can have a major impact on an organization’s IT infrastructure.
Previously, Internet-connected devices mainly relied on cloud computing. However, lately, IoT manufacturers and software developers have realized that moving computations and analytics to the devices can provide a host of benefits. This on-device approach allows an organization to minimize latency for their critical systems and reduce cloud computing dependence. This way, they can manage the massive amount of data produced by IoT in a better way.
For instance, consider the Nest Cam IQ security cameras. It employs on-device vision processing to detect motion, identify family members, and generates alerts as soon as an unfamiliar party fails to fit the pre-defined parameters. The camera performs computer vision tasks, which minimizes the amount of cloud storage, cloud processing, and bandwidth used. Moreover, on-device processing boosts the frequency of alerts while minimizing the chances of recurrent and annoying false alarms.
What Is Edge Computing?
Edge computing is a type of distributed computing topology that processes information close to the edge – where people and things consume or produce that information.
In essence, edge computing moves data storage and computation closer to the device that collects it in the first place, instead of relying on a primary or central location that is often far away. The vision behind this approach is to resolve latency issues that can impact the performance of an application. Additionally, organizations can increase their savings by bringing processing to the local level as it reduces the amount of data that has to be processed in a cloud-based or centralized location. Edge computing was created because of the rapid growth of IoT technology, which is connected to the web for collecting information from the cloud and delivering that data back to the cloud. Various IoT devices produce large amounts of data while working on their operations.
How IoT and Edge Are Related?
IoT and edge computing are related because edge computing solves many IoT issues, including latency and network congestion.
The higher density of IoT devices, the sheer amount of data generated, and performance requirements cause network congestion. The need for a reliable connection and low latency for critical IoT devices put lots of strain on the network. Different telecoms are developing their own IoT networks that can enhance the support for many online devices.
Edge computing puts computing, networking, and storage resources close to the end user. This strategic placement of resources nearer to IoT devices means that devices no longer have to send traffic to a central data center. This minimizes the bandwidth and enhances performance.
Experts predict that IoT devices will be mainly supported by the 5G network as soon as the latter becomes a mature technology. One of the vital parts of the 5G architecture is edge computing functionalities in the network nodes, especially for the compact cell base stations in the densely populated urban regions.
Benefits of Edge Computing The issues edge addresses for IoT devices include the following:
Low Latency
Usually, IoT devices are low-power devices without heavy storage or compute capabilities. A low-latency connection refers to when a device can gather data, transfer it to an edge device, perform processing at the edge, and receive the data back without the end user experiencing any lag.
Connection Reliability
While IoT devices move from cool gadgets to mission-critical infrastructure, a reliable connection is crucial. Environments with heterogeneous sensors like factors and smart cities employ edge computing for improving packet transmission. This report suggests that edge devices can be used to detect the quality of sensor connections. They can determine how many sensor nodes are missing packet transmissions multiple times because of poor links.
When that happens, the edge devices rely on their advanced radio power for the transmission of packets over a better link than the low-power radios on sensors.
Data Management
IoT devices generated voluminous amounts of data, especially from the sensors. Before this data is used, it must go through in-depth analysis. Edge computing can do this job by analyzing a massive amount of data produced by monitoring. But, do keep in mind that there are certain limitations with the edge, especially while having exceptionally vast volumes of data.
The Security Dilemma
As is the case with various new technologies, addressing one problem can create another. From a cybersecurity perspective, data at the edge can pose risks, particularly when different devices handling it are not as secure as a cloud-based or centralized system. While the number of IoT devices increases, it is important that organizations understand the potential security risks circling these devices and ensure that these systems are protected. This includes using suitable access control methods, VPN tunneling, and data encryption.
Lastly, varying device requirements for network connectivity, electricity, and processing power can affect an edge device’s reliability. This makes failover management and redundancy important for devices that process data at the edge to ensure that the data is processed and delivered correctly while a single node goes down. If you deal in edge computing, computer networking, IT support, and services then you can hire us.