Edge computing definition: Providing tactical power for the future

20 April 2021

Edge computing definition according to the industry experts is considered to be a framework revolution placed near the data source. No longer users are required to rely upon Cloud or its data centres for gathering crucial information. Rather, Cloud is termed to be a computer application with users being provided with clear access to a variety of computers, IT related information and software applications over the web. It is done through network connection using different data centres. Presently, it is used to enter data in the cloud systems. Data gathered through online resources like IoT (Internet of Things) devices gets packaged for the purpose of packaging. Then it is analyzed before data is sent to the data centre or a cloud at the edge. IoT is crucial to collect precious data since this system helps interconnect as well as create unique identifiers especially for objects, digital machines, people, animals and computing devices. Data stored in the unique identifiers are said to be transferred over a large network, without requiring human-to-computer or human-to-human interaction.

What are the benefits to be derived?

The user can derive several benefits by using edge computing definition. Using this advanced technology, users can ensure available applications offering improved performance. The apps on edge of the edge computing device can attain reduced latency levels. This is something not abided by data centres or cloud. Users similarly can acquire from the local device a real-time data analysis, located close to its source. This helps processing time to reduce significantly as data is not required to be sent to the data centres or a Cloud.

Moreover, single network is not used any more to transmit crucial information to data centres or a cloud, thereby reducing network traffic. Every computing source tends to have own network quite near its source, thereby reducing significantly the traffic.

Moreover, only data which requires to be analyzed gets transferred. By using edge computing, cloud operating expenses reduces significantly including that of its data centres. Only smaller local devices are to be managed, thus reducing overall expenses. It also helps especially during intermittent and poor connection via IoT since connectivity is not desired to process as well as transmit data. Connection is not desired to make decisions without waiting to get command from another place. This, in turn, reduces time loss and travel time. Similarly, users can derive more reliability and security as data gets transmitted through edge devices much closer to edge. As there is no interference noticed of data centres or a cloud, data gets transferred smoothly. Hence, less data requires being stored, thereby making life difficult for the hackers.


IoT (Internet of Things) is witnessing a big shift, thus moving computing towards using intelligent devices and local networks through edge computing. Collected data analysis close to the source is considered to be a profound shift especially for machine learning. Since its source is very near, users can derive minimum latency benefits. Latency is reduced as data is not required to be sent as well as analyzed at cloud, thus reducing data transfer cost over a networking including managing of high-end centralized servers.