Edge Computing
What is Edge Computing?
Before introducing the term and the concept of Edge computing, we must first understand the meaning of “edge.” The term “edge” is both ambiguous and all-encompassing. This word “edge” generates a buzz similar to that of the cloud and IoT. Edge computing helps allocate a computing framework that facilitates enterprise applications that are situated close to data sources, such as local edge servers and IoT devices. These data sources offer various benefits to organizations, including improved response times, ample bandwidth availability, and faster insights.
In other words, it entails computing that occurs either at or near the source of data. It means that the cloud is either closer to you or coming to you, rather than being distant and inaccessible.
Edge devices consist of three layers: the edge layer, the fog layer, and the cloud layer. Initially, edge devices communicate with the edge gateway in the edge layer. Subsequently, the signal is relayed from the edge gateway to the fog nodes in the fog layer. Finally, this data is transferred to the cloud or data center in the cloud layer. Mobile edge or edge computing takes place on advanced networks like 5G, enabling extensive data analysis and faster, enhanced customer experiences, quicker response times, and deeper insights.
The Benefits of Edge Computing
There are five significant benefits of edge computing: security, speed, cost savings, scalability, and bandwidth efficiency. Let’s discuss these advantages in more detail.
Security
Having less data traversing the entire network enhances security. When all data is stored in one location, the main focus is on security, safeguarding the local data of smart product manufacturers. With more distributed data on the network, the risk of a breach increases, even if an appliance is compromised. This also assists organizations in addressing local compliance and data autonomy issues.
Speed
Edge computing reduces the burden on an organization’s network traffic, which, in turn, enhances the performance of its services and applications. Speed is crucial for essential business operations, especially for companies offering data-driven services. Slow speeds can dissatisfy customers and negatively impact a company’s reputation.
Cost Savings
Not all data within an organization holds the same value, and categorizing data for management purposes can result in cost savings. Edge computing allows data to be categorized, reducing the need for costly bandwidth and eliminating redundant storage costs.
Bandwidth Efficiency
Many organizations use significant bandwidth for less important data. Edge computing helps optimize bandwidth usage by prioritizing critical data transmission.
Versatility
Edge computing’s scalability is vital for versatility. It empowers IoT devices to collect vast amounts of data continuously, ensuring data is available for further analysis, eliminating the need for constant interaction with cloud servers.
Offline Operation
This benefit is one of the best benefit of edge computing, it allows the application to manage even when there is no internet connection or central data center. User can utilize it in any places either having internet services or not. In the other words we can say it provide the continuity of services in remote or isolated location.
Uses Cases Of Edge Computing
Some important uses cases of Edge computing are as follow:
Industrial Automation: In the industrial and in manufacturing line, edge computing is utilized for the actual time monitoring and processes and control of machines. It allow predictive maintenance, optimization of manufacturing operations and quality control.
Healthcare: Edge computing is utilized in healthcare to monitoring the patient for remote basis, telemedicine’s and using health devices and it also provide the correct data analysis and some quick alert to the tough condition arise from medical.
Agriculture: Edge computing also plays an important role in agriculture to monitor crop health, soil conditions and whether in actual time. It also help in allotment of resources as well as doing farming practices. It helps in different type of agriculture such as in Precision Agriculture and in this type soil and crop health monitoring etc. are included and it is helpful in every types of agriculture.
Though there are many use cases for several industries, we have mentioned few ones to you and these are industrial automation, healthcare, agriculture
Image Credit:https://innovationatwork.ieee.org/real-life-edge-computing-use-cases/
In the above image you have seen the real-life use cases for Edge Computing. There are many loT devices that is manage by cloud and data center.
Edge Computing vs. Cloud Computing
Image Credit:https://www.orientsoftware.com/blog/edge-computing-vs-cloud-computing/
As you have seen the differences in the above images, now you will see the differences as mentioned below :
| S.No. | Edge Computing | Cloud Computing |
|---|---|---|
| 1 | Its platform is its own devices. | It operates in a cloud platform, such as Amazon EC2, Google Cloud, etc. |
| 2 | Normal reaction time is in milliseconds. | Normal reaction time is also quick, but not as fast as edge computing, typically in minutes or days. |
| 3 | Concerned with networking operations and deploying data handling near the network’s edge. | Provides computing resources on demand, including storage, databases, servers, etc. |
| 4 | Requires less bandwidth compared to the cloud. | Cloud computing demands more bandwidth. |
| 5 | Access occurs at the end of the appliance, such as the smart sensor. | Access occurs on the main server and headquarters. |
| 6 | Emphasizes robust security. | Does not emphasize robust security and safety. |
Conclusion:
Edge computing allows the deployment of computing resources closer to data sources, such as local edge servers and IoT devices, resulting in advantages like improved response times, ample bandwidth availability, and faster insights. Throughout the article, we’ve explored the fundamental concept of edge computing, its benefits, and its comparison with cloud computing. We’ve also examined its diverse applications across various industries, including healthcare and autonomous vehicles.
