What is Edge Computing

Edge Computing enables data to be analyzed, processed and transferred at the edge of the network instead of being transmitted to the centralized data center (Cloud). Or edge computing refers to bringing computing such as processing, analyzing, and storing data closer to where it is generated to enable rapid, real-time analysis and response.

Edge computing means the computations are less at the cloud and maximum at local places such as on a local computer, Internet of things (IoT) device, or an edge server. Edge Computing minimizes the long-distance communication between the client and the server and increases the response time and real-time analysis.

Edge or Network Edge: The part of the network where the devices generate or consume data. The network edge is where the local network contains the devices that communicate with the Internet. Local computers, servers, and the Internet of things (IoT)are considered the edge of the network.

What makes Edge Computing Different from Other Computing Models

In cloud computing, all the data generated are stored at a centralized data center known as the cloud; all the computations occur at the cloud servers. The computation occurs on one isolated computer in early computing by running the centralized application.

In personal computing, all the computation occurs at the personal computer using the decentralized application. In comparison, all the computation occurs near where it is generated

in edge computing.

Advantages of Edge Computing

• Cheap: Edge computing minimizes the bandwidth use and server resources as IoT devices are being installed rapidly, such as smart cameras, printers, toasters at houses worldwide. The server's bandwidth and resources are finite and cost a lot of money, and edge computing helps move a significant amount of computation at the edge. Some of the advantages of edge computing are listed below:
• Rapid and Real-time analysis: When a device tries to connect with a long-distance server faces a delay in data transmission, leading to big data losses and wrong computation; moving the processes at the edge reduces delay. For example, two computers are trying to connect with each other using a long-distance server, a message sent by a computer can be delayed, and a second message can be reached at the other end first. The data processed by the second computer gives a wrong result.

Similarly, when multiple web applications try to run processes that have to communicate with external servers, they can face some delays depending on the bandwidth available. These delays can be reduced by bringing more processes closer to the network edge. Bring processes near the network’s edge gives the benefits of rapid and real-time analysis benefits.

• New Features and Functions: Edge computing gives new functionalities that were not available with other computing models. For example, a multinational company with multiple branches in different countries and one centralized data center. Each branch can use edge computing to process and analyze their data at the edge, giving a real-time analysis to reduce the latency by decreasing the use of the server’s bandwidth and resources. This will also decrease the maintenance cost of the cloud server.

Flaws of the Edge Computing

Edge computing comes with multiple opportunities for cyber attackers. The rapid installation of IoT devices at the network edge increases the opportunities for cyber attackers to perform their desired malicious activities and compromise these devices.

Also, edge computing requires more local hardware to be installed at the edge. For example, installing a traffic camera requires a built-in computer to send the raw video to the web server, process and run the motion detection algorithm, and use a powerful computer. But the cost of doing this is much less, which results in building smarter devices. The use of local hardware can be reduced by taking advantage of edge servers.